References
Abrahamsson, Dimitri, Christopher L. Brueck, Carsten Prasse, Dimitra A. Lambropoulou, Lelouda-Athanasia Koronaiou, Miaomiao Wang, June-Soo Park, and Tracey J. Woodruff. 2023. “Extracting Structural Information from Physicochemical Property Measurements Using Machine Learning-A New Approach for Structure Elucidation in Non-targeted Analysis.” Environmental Science & Technology, September. https://doi.org/10.1021/acs.est.3c03003.
Adams, Kendra J., Brian Pratt, Neelanjan Bose, Laura G. Dubois, Lisa St John-Williams, Kevin M. Perrott, Karina Ky, et al. 2020. “Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics.” Journal of Proteome Research 19 (4): 1447–58. https://doi.org/10.1021/acs.jproteome.9b00640.
Aguilar-Mogas, Antoni, Marta Sales-Pardo, Miriam Navarro, Roger Guimerà, and Oscar Yanes. 2017. “iMet: A Network-Based Computational Tool To Assist in the Annotation of Metabolites from Tandem Mass Spectra.” Analytical Chemistry 89 (6): 3474–82. https://doi.org/10.1021/acs.analchem.6b04512.
Alden, Nicholas, Smitha Krishnan, Vladimir Porokhin, Ravali Raju, Kyle McElearney, Alan Gilbert, and Kyongbum Lee. 2017. “Biologically Consistent Annotation of Metabolomics Data.” Analytical Chemistry, November. https://doi.org/10.1021/acs.analchem.7b02162.
Ali, Ahmed, Yasmine Abouleila, Yoshihiro Shimizu, Eiso Hiyama, Samy Emara, Alireza Mashaghi, and Thomas Hankemeier. 2019. “Single-Cell Metabolomics by Mass Spectrometry: Advances, Challenges, and Future Applications.” TrAC Trends in Analytical Chemistry 120 (November): 115436. https://doi.org/10.1016/j.trac.2019.02.033.
Alka, Oliver, Timo Sachsenberg, Leon Bichmann, Julianus Pfeuffer, Hendrik Weisser, Samuel Wein, Eugen Netz, Marc Rurik, Oliver Kohlbacher, and Hannes Röst. 2020. “CHAPTER 6:OpenMS and KNIME for Mass Spectrometry Data Processing.” In Processing Metabolomics and Proteomics Data with Open Software, 201–31. https://doi.org/10.1039/9781788019880-00201.
Alka, Oliver, Premy Shanthamoorthy, Michael Witting, Karin Kleigrewe, Oliver Kohlbacher, and Hannes L. Röst. 2022. “DIAMetAlyzer Allows Automated False-Discovery Rate-Controlled Analysis for Data-Independent Acquisition in Metabolomics.” Nature Communications 13 (1): 1347. https://doi.org/10.1038/s41467-022-29006-z.
Allam-Ndoul, Bénédicte, Frédéric Guénard, Véronique Garneau, Hubert Cormier, Olivier Barbier, Louis Pérusse, and Marie-Claude Vohl. 2016. “Association Between Metabolite Profiles, Metabolic Syndrome and Obesity Status.” Nutrients 8 (6): 324. https://doi.org/10.3390/nu8060324.
Allard, Pierre-Marie, Grégory Genta-Jouve, and Jean-Luc Wolfender. 2017. “Deep Metabolome Annotation in Natural Products Research: Towards a Virtuous Cycle in Metabolite Identification.” Current Opinion in Chemical Biology, Omics, 36 (February): 40–49. https://doi.org/10.1016/j.cbpa.2016.12.022.
Allen, Felicity, Allison Pon, Michael Wilson, Russ Greiner, and David Wishart. 2014. “CFM-ID: A Web Server for Annotation, Spectrum Prediction and Metabolite Identification from Tandem Mass Spectra.” Nucleic Acids Research 42 (W1): W94–99. https://doi.org/10.1093/nar/gku436.
Alonso, Arnald, Sara Marsal, and Antonio Julià. 2015. “Analytical Methods in Untargeted Metabolomics: State of the Art in 2015.” Frontiers in Bioengineering and Biotechnology 3 (March). https://doi.org/10.3389/fbioe.2015.00023.
Anderson, Brady G., Alexander Raskind, Hani Habra, Robert T. Kennedy, and Charles R. Evans. 2021. “Modifying Chromatography Conditions for Improved Unknown Feature Identification in Untargeted Metabolomics.” Analytical Chemistry 93 (48): 15840–49. https://doi.org/10.1021/acs.analchem.1c02149.
Andersson, Martin. 2009. “A Comparison of Nine PLS1 Algorithms.” Journal of Chemometrics 23 (10): 518–29. https://doi.org/10.1002/cem.1248.
Aron, Allegra T., Emily C. Gentry, Kerry L. McPhail, Louis-Félix Nothias, Mélissa Nothias-Esposito, Amina Bouslimani, Daniel Petras, et al. 2020. “Reproducible Molecular Networking of Untargeted Mass Spectrometry Data Using GNPS.” Nature Protocols 15 (6): 1954–91. https://doi.org/10.1038/s41596-020-0317-5.
Bach, Eric, Emma L. Schymanski, and Juho Rousu. 2022. “Joint Structural Annotation of Small Molecules Using Liquid Chromatography Retention Order and Tandem Mass Spectrometry Data.” Nature Machine Intelligence 4 (12): 1224–37. https://doi.org/10.1038/s42256-022-00577-2.
Bai, Caihong, Suyun Xu, Jingyi Tang, Yuxi Zhang, Jiahui Yang, and Kaifeng Hu. 2022. “A ‘Shape-Orientated’ Algorithm Employing an Adapted Marr Wavelet and Shape Matching Index Improves the Performance of Continuous Wavelet Transform for Chromatographic Peak Detection and Quantification.” Journal of Chromatography A 1673 (June): 463086. https://doi.org/10.1016/j.chroma.2022.463086.
Baker, Monya. 2011. “Metabolomics: From Small Molecules to Big Ideas.” Nature Methods 8 (2): 117–21. https://doi.org/10.1038/nmeth0211-117.
Baran, Richard, and Trent R. Northen. 2013. “Robust Automated Mass Spectra Interpretation and Chemical Formula Calculation Using Mixed Integer Linear Programming.” Analytical Chemistry 85 (20): 9777–84. https://doi.org/10.1021/ac402180c.
Barbier Saint Hilaire, Pierre, Ulli M. Hohenester, Benoit Colsch, Jean-Claude Tabet, Christophe Junot, and François Fenaille. 2018. “Evaluation of the High-Field Orbitrap Fusion for Compound Annotation in Metabolomics.” Analytical Chemistry 90 (5): 3030–35. https://doi.org/10.1021/acs.analchem.7b05372.
Barnes, Stephen, H. Paul Benton, Krista Casazza, Sara J. Cooper, Xiangqin Cui, Xiuxia Du, Jeffrey Engler, et al. 2016a. “Training in Metabolomics Research. I. Designing the Experiment, Collecting and Extracting Samples and Generating Metabolomics Data.” Journal of Mass Spectrometry 51 (7): 461–75. https://doi.org/10.1002/jms.3782.
———, et al. 2016b. “Training in Metabolomics Research. II. Processing and Statistical Analysis of Metabolomics Data, Metabolite Identification, Pathway Analysis, Applications of Metabolomics and Its Future.” Journal of Mass Spectrometry 51 (8): 535–48. https://doi.org/10.1002/jms.3780.
Barranco-Altirriba, Maria, Pol Solà-Santos, Sergio Picart-Armada, Samir Kanaan-Izquierdo, Jordi Fonollosa, and Alexandre Perera-Lluna. 2021. “mWISE: An Algorithm for Context-Based Annotation of Liquid Chromatography–Mass Spectrometry Features Through Diffusion in Graphs.” Analytical Chemistry 93 (31): 10772–78. https://doi.org/10.1021/acs.analchem.1c00238.
Basu, Sumanta, William Duren, Charles R. Evans, Charles F. Burant, George Michailidis, and Alla Karnovsky. 2017. “Sparse Network Modeling and Metscape-Based Visualization Methods for the Analysis of Large-Scale Metabolomics Data.” Bioinformatics 33 (10): 1545–53. https://doi.org/10.1093/bioinformatics/btx012.
Baygi, Sadjad Fakouri, Sanjay K. Banerjee, Praloy Chakraborty, Yashwant Kumar, and Dinesh Kumar Barupal. 2022. “IDSL.UFA Assigns High-Confidence Molecular Formula Annotations for Untargeted LC/HRMS Data Sets in Metabolomics and Exposomics.” Analytical Chemistry 94 (39): 13315–22. https://doi.org/10.1021/acs.analchem.2c00563.
Baygi, Sadjad Fakouri, Yashwant Kumar, and Dinesh Kumar Barupal. 2023. “IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets.” IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets, June. https://doi.org/10.1021/acs.analchem.3c00376.
Beale, David J., Farhana R. Pinu, Konstantinos A. Kouremenos, Mahesha M. Poojary, Vinod K. Narayana, Berin A. Boughton, Komal Kanojia, Saravanan Dayalan, Oliver A. H. Jones, and Daniel A. Dias. 2018. “Review of Recent Developments in GC–MS Approaches to Metabolomics-Based Research.” Metabolomics 14 (11): 152. https://doi.org/10.1007/s11306-018-1449-2.
Begou, O., H. G. Gika, I. D. Wilson, and G. Theodoridis. 2017. “Hyphenated MS-based Targeted Approaches in Metabolomics.” Analyst 142 (17): 3079–3100. https://doi.org/10.1039/C7AN00812K.
Benjamini, Yoav, and Yosef Hochberg. 1995. “Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing.” Journal of the Royal Statistical Society. Series B (Methodological) 57 (1): 289–300. https://www.jstor.org/stable/2346101.
Bennett, Bryson D., Elizabeth H. Kimball, Melissa Gao, Robin Osterhout, Stephen J. Van Dien, and Joshua D. Rabinowitz. 2009. “Absolute Metabolite Concentrations and Implied Enzyme Active Site Occupancy in Escherichia Coli.” Nature Chemical Biology 5 (8): 593–99. https://doi.org/10.1038/nchembio.186.
Bernardo-Bermejo, Samuel, Jingchuan Xue, Linh Hoang, Elizabeth Billings, Bill Webb, M. Willy Honders, Sanne Venneker, et al. 2023. “Quantitative Multiple Fragment Monitoring with Enhanced in-Source Fragmentation/Annotation Mass Spectrometry.” Nature Protocols, February, 1–20. https://doi.org/10.1038/s41596-023-00803-0.
Bertsch, Andreas, Clemens Gröpl, Knut Reinert, and Oliver Kohlbacher. 2011. “OpenMS and TOPP: Open Source Software for LC-MS Data Analysis.” In Data Mining in Proteomics: From Standards to Applications, edited by Michael Hamacher, Martin Eisenacher, and Christian Stephan, 353–67. Methods in Molecular Biology. Totowa, NJ: Humana Press. https://doi.org/10.1007/978-1-60761-987-1_23.
Bijttebier, Sebastiaan, Anastasia Van der Auwera, Kenn Foubert, Stefan Voorspoels, Luc Pieters, and Sandra Apers. 2016. “Bridging the Gap Between Comprehensive Extraction Protocols in Plant Metabolomics Studies and Method Validation.” Analytica Chimica Acta 935 (September): 136–50. https://doi.org/10.1016/j.aca.2016.06.047.
Bilbao, Aivett, Nathalie Munoz, Joonhoon Kim, Daniel J. Orton, Yuqian Gao, Kunal Poorey, Kyle R. Pomraning, et al. 2023. “PeakDecoder Enables Machine Learning-Based Metabolite Annotation and Accurate Profiling in Multidimensional Mass Spectrometry Measurements.” Nature Communications 14 (1): 2461. https://doi.org/10.1038/s41467-023-37031-9.
Bilbao, Aivett, Emmanuel Varesio, Jeremy Luban, Caterina Strambio-De-Castillia, Gérard Hopfgartner, Markus Müller, and Frédérique Lisacek. 2015. “Processing Strategies and Software Solutions for Data-Independent Acquisition in Mass Spectrometry.” PROTEOMICS 15 (5-6): 964–80. https://doi.org/10.1002/pmic.201400323.
Bittremieux, Wout, Nicole E. Avalon, Sydney P. Thomas, Sarvar A. Kakhkhorov, Alexander A. Aksenov, Paulo Wender P. Gomes, Christine M. Aceves, et al. 2023. “Open Access Repository-Scale Propagated Nearest Neighbor Suspect Spectral Library for Untargeted Metabolomics.” Nature Communications 14 (1): 8488. https://doi.org/10.1038/s41467-023-44035-y.
Bittremieux, Wout, Robin Schmid, Florian Huber, Justin J. J. van der Hooft, Mingxun Wang, and Pieter C. Dorrestein. 2022. “Comparison of Cosine, Modified Cosine, and Neutral Loss Based Spectrum Alignment For Discovery of Structurally Related Molecules.” Journal of the American Society for Mass Spectrometry 33 (9): 1733–44. https://doi.org/10.1021/jasms.2c00153.
Blaise, Benjamin J. 2013. “Data-Driven Sample Size Determination for Metabolic Phenotyping Studies.” Analytical Chemistry 85 (19): 8943–50. https://doi.org/10.1021/ac4022314.
Blaise, Benjamin J., Gonçalo D. S. Correia, Gordon A. Haggart, Izabella Surowiec, Caroline Sands, Matthew R. Lewis, Jake T. M. Pearce, et al. 2021. “Statistical Analysis in Metabolic Phenotyping.” Nature Protocols, July, 1–28. https://doi.org/10.1038/s41596-021-00579-1.
Blaise, Benjamin J., Gonçalo Correia, Adrienne Tin, J. Hunter Young, Anne-Claire Vergnaud, Matthew Lewis, Jake T. M. Pearce, et al. 2016. “Power Analysis and Sample Size Determination in Metabolic Phenotyping.” Analytical Chemistry 88 (10): 5179–88. https://doi.org/10.1021/acs.analchem.6b00188.
Blaženović, Ivana, Tobias Kind, Hrvoje Torbašinović, Slobodan Obrenović, Sajjan S. Mehta, Hiroshi Tsugawa, Tobias Wermuth, et al. 2017. “Comprehensive Comparison of in Silico MS/MS Fragmentation Tools of the CASMI Contest: Database Boosting Is Needed to Achieve 93% Accuracy.” Journal of Cheminformatics 9 (1): 32. https://doi.org/10.1186/s13321-017-0219-x.
Bonini, Paolo, Tobias Kind, Hiroshi Tsugawa, Dinesh Kumar Barupal, and Oliver Fiehn. 2020. “Retip: Retention Time Prediction for Compound Annotation in Untargeted Metabolomics.” Analytical Chemistry 92 (11): 7515–22. https://doi.org/10.1021/acs.analchem.9b05765.
Bonnefille, Bénilde, Oskar Karlsson, May Britt Rian, Rubhana Raqib, Faruque Parvez, Stefano Papazian, M. Sirajul Islam, and Jonathan W. Martin. 2023. “Nontarget Analysis of Polluted Surface Waters in Bangladesh Using Open Science Workflows.” Environmental Science & Technology, April. https://doi.org/10.1021/acs.est.2c08200.
Bonner, Ron, and Gérard Hopfgartner. 2018. “SWATH Data Independent Acquisition Mass Spectrometry for Metabolomics.” TrAC Trends in Analytical Chemistry, October. https://doi.org/10.1016/j.trac.2018.10.014.
Box, George E. P., J. Stuart Hunter, and William G. Hunter. 2005. Statistics for Experimenters. Wiley-Interscience.
Brereton, Richard G., and Gavin R. Lloyd. 2018. “Partial Least Squares Discriminant Analysis for Chemometrics and Metabolomics: How Scores, Loadings, and Weights Differ According to Two Common Algorithms.” Journal of Chemometrics 32 (4): e3028. https://doi.org/10.1002/cem.3028.
Broadhurst, David, Royston Goodacre, Stacey N. Reinke, Julia Kuligowski, Ian D. Wilson, Matthew R. Lewis, and Warwick B. Dunn. 2018. “Guidelines and Considerations for the Use of System Suitability and Quality Control Samples in Mass Spectrometry Assays Applied in Untargeted Clinical Metabolomic Studies.” Metabolomics 14 (6). https://doi.org/10.1007/s11306-018-1367-3.
Broeckling, C. D., F. A. Afsar, S. Neumann, A. Ben-Hur, and J. E. Prenni. 2014. “RAMClust: A Novel Feature Clustering Method Enables Spectral-Matching-Based Annotation for Metabolomics Data.” Analytical Chemistry 86 (14): 6812–17. https://doi.org/10.1021/ac501530d.
Broeckling, Corey D., Richard D. Beger, Leo L. Cheng, Raquel Cumeras, Daniel J. Cuthbertson, Surendra Dasari, W. Clay Davis, et al. 2023. “Current Practices in LC-MS Untargeted Metabolomics: A Scoping Review on the Use of Pooled Quality Control Samples.” Analytical Chemistry 95 (51): 18645–54. https://doi.org/10.1021/acs.analchem.3c02924.
Broeckling, Corey D., Andrea Ganna, Mark Layer, Kevin Brown, Ben Sutton, Erik Ingelsson, Graham Peers, and Jessica E. Prenni. 2016. “Enabling Efficient and Confident Annotation of LC-MS Metabolomics Data Through MS1 Spectrum and Time Prediction.” Analytical Chemistry 88 (18): 9226–34. https://doi.org/10.1021/acs.analchem.6b02479.
Bundy, Jacob G., Matthew P. Davey, and Mark R. Viant. 2009. “Environmental Metabolomics: A Critical Review and Future Perspectives.” Metabolomics 5 (1): 3. https://doi.org/10.1007/s11306-008-0152-0.
Cai, Jingwei, and Zhengyin Yan. 2021. “Re-Examining the Impact of Minimal Scans in Liquid Chromatography–Mass Spectrometry Analysis.” Journal of the American Society for Mass Spectrometry, June. https://doi.org/10.1021/jasms.1c00073.
Cai, Qingpo, Jessica A. Alvarez, Jian Kang, and Tianwei Yu. 2017. “Network Marker Selection for Untargeted LC–MS Metabolomics Data.” Journal of Proteome Research 16 (3): 1261–69. https://doi.org/10.1021/acs.jproteome.6b00861.
Cajka, Tomas, and Oliver Fiehn. 2016. “Toward Merging Untargeted and Targeted Methods in Mass Spectrometry-Based Metabolomics and Lipidomics.” Analytical Chemistry 88 (1): 524–45. https://doi.org/10.1021/acs.analchem.5b04491.
Calbiani, F., M. Careri, L. Elviri, A. Mangia, and I. Zagnoni. 2006. “Matrix Effects on Accurate Mass Measurements of Low-Molecular Weight Compounds Using Liquid Chromatography-Electrospray-Quadrupole Time-of-Flight Mass Spectrometry.” Journal of Mass Spectrometry 41 (3): 289–94. https://doi.org/10.1002/jms.984.
Carroll, Adam J., Murray R. Badger, and A. Harvey Millar. 2010. “The MetabolomeExpress Project: Enabling Web-Based Processing, Analysis and Transparent Dissemination of GC/MS Metabolomics Datasets.” BMC Bioinformatics 11 (1): 376. https://doi.org/10.1186/1471-2105-11-376.
Castro-Puyana, María, Raquel Pérez-Míguez, Lidia Montero, and Miguel Herrero. 2017. “Application of Mass Spectrometry-Based Metabolomics Approaches for Food Safety, Quality and Traceability.” TrAC Trends in Analytical Chemistry 93 (August): 102–18. https://doi.org/10.1016/j.trac.2017.05.004.
Chaker, Jade, David Møbjerg Kristensen, Thorhallur Ingi Halldorsson, Sjurdur Frodi Olsen, Christine Monfort, Cécile Chevrier, Bernard Jégou, and Arthur David. 2022. “Comprehensive Evaluation of Blood Plasma and Serum Sample Preparations for HRMS-Based Chemical Exposomics: Overlaps and Specificities.” Analytical Chemistry 94 (2): 866–74. https://doi.org/10.1021/acs.analchem.1c03638.
Chaleckis, Romanas, Isabel Meister, Pei Zhang, and Craig E Wheelock. 2019. “Challenges, Progress and Promises of Metabolite Annotation for LC–MS-based Metabolomics.” Current Opinion in Biotechnology, Analytical Biotechnology, 55 (February): 44–50. https://doi.org/10.1016/j.copbio.2018.07.010.
Chambers, Matthew C., Brendan Maclean, Robert Burke, Dario Amodei, Daniel L. Ruderman, Steffen Neumann, Laurent Gatto, et al. 2012. “A Cross-Platform Toolkit for Mass Spectrometry and Proteomics.” Nature Biotechnology 30 (October): 918–20. https://doi.org/10.1038/nbt.2377.
Chang, Hui-Yin, Ching-Tai Chen, T. Mamie Lih, Ke-Shiuan Lynn, Chiun-Gung Juo, Wen-Lian Hsu, and Ting-Yi Sung. 2016. “iMet-Q: A User-Friendly Tool for Label-Free Metabolomics Quantitation Using Dynamic Peak-Width Determination.” PLOS ONE 11 (1): e0146112. https://doi.org/10.1371/journal.pone.0146112.
Chang, Hui-Yin, Sean M. Colby, Xiuxia Du, Javier D. Gomez, Maximilian J. Helf, Katerina Kechris, Christine R. Kirkpatrick, et al. 2021. “A Practical Guide to Metabolomics Software Development.” Analytical Chemistry 93 (4): 1912–23. https://doi.org/10.1021/acs.analchem.0c03581.
Charbonnet, Joseph A., Carrie A. McDonough, Feng Xiao, Trever Schwichtenberg, Dunping Cao, Sarit Kaserzon, Kevin V. Thomas, et al. 2022. “Communicating Confidence of Per- and Polyfluoroalkyl Substance Identification via High-Resolution Mass Spectrometry.” Environmental Science & Technology Letters, May. https://doi.org/10.1021/acs.estlett.2c00206.
Chen, Gengbo, Scott Walmsley, Gemmy C. M. Cheung, Liyan Chen, Ching-Yu Cheng, Roger W. Beuerman, Tien Yin Wong, Lei Zhou, and Hyungwon Choi. 2017. “Customized Consensus Spectral Library Building for Untargeted Quantitative Metabolomics Analysis with Data Independent Acquisition Mass Spectrometry and MetaboDIA Workflow.” Analytical Chemistry 89 (9): 4897–4906. https://doi.org/10.1021/acs.analchem.6b05006.
Chen, Li, Wenyun Lu, Lin Wang, Xi Xing, Ziyang Chen, Xin Teng, Xianfeng Zeng, et al. 2021. “Metabolite Discovery Through Global Annotation of Untargeted Metabolomics Data.” Nature Methods 18 (11): 1377–85. https://doi.org/10.1038/s41592-021-01303-3.
Chen, Yanhua, Zhi Zhou, Wei Yang, Nan Bi, Jing Xu, Jiuming He, Ruiping Zhang, Lvhua Wang, and Zeper Abliz. 2017. “Development of a Data-Independent Targeted Metabolomics Method for Relative Quantification Using Liquid Chromatography Coupled with Tandem Mass Spectrometry.” Analytical Chemistry 89 (13): 6954–62. https://doi.org/10.1021/acs.analchem.6b04727.
Cheng, Susan, Svati H. Shah, Elizabeth J. Corwin, Oliver Fiehn, Robert L. Fitzgerald, Robert E. Gerszten, Thomas Illig, et al. 2017. “Potential Impact and Study Considerations of Metabolomics in Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association.” Circulation: Cardiovascular Genetics 10 (2): e000032. https://doi.org/10.1161/HCG.0000000000000032.
Choi, Meena, Ching-Yun Chang, Timothy Clough, Daniel Broudy, Trevor Killeen, Brendan MacLean, and Olga Vitek. 2014. “MSstats: An R Package for Statistical Analysis of Quantitative Mass Spectrometry-Based Proteomic Experiments.” Bioinformatics 30 (17): 2524–26. https://doi.org/10.1093/bioinformatics/btu305.
Chokkathukalam, Achuthanunni, Andris Jankevics, Darren J. Creek, Fiona Achcar, Michael P. Barrett, and Rainer Breitling. 2013. “mzMatch–ISO: An R Tool for the Annotation and Relative Quantification of Isotope-Labelled Mass Spectrometry Data.” Bioinformatics 29 (2): 281–83. https://doi.org/10.1093/bioinformatics/bts674.
Chong, Jasmine, David S. Wishart, and Jianguo Xia. 2019. “Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis.” Current Protocols in Bioinformatics 68 (1): e86. https://doi.org/10.1002/cpbi.86.
Clasquin, Michelle F., Eugene Melamud, and Joshua D. Rabinowitz. 2012. “LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine.” Current Protocols in Bioinformatics 37 (1): 14.11.1–23. https://doi.org/10.1002/0471250953.bi1411s37.
Climaco Pinto, Rui, Ibrahim Karaman, Matthew R. Lewis, Jenny Hällqvist, Manuja Kaluarachchi, Gonçalo Graça, Elena Chekmeneva, et al. 2022. “Finding Correspondence Between Metabolomic Features in Untargeted Liquid Chromatography–Mass Spectrometry Metabolomics Datasets.” Analytical Chemistry 94 (14): 5493–503. https://doi.org/10.1021/acs.analchem.1c03592.
Codrean, S., B. Kruit, N. Meekel, D. Vughs, and F. Béen. 2023. “Predicting the Diagnostic Information of Tandem Mass Spectra of Environmentally Relevant Compounds Using Machine Learning.” Analytical Chemistry, October. https://doi.org/10.1021/acs.analchem.3c03470.
Colby, Sean M., Christine H. Chang, Jessica L. Bade, Jamie R. Nunez, Madison R. Blumer, Daniel J. Orton, Kent J. Bloodsworth, et al. 2022. “DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data.” Analytical Chemistry 94 (16): 6130–38. https://doi.org/10.1021/acs.analchem.1c05017.
Considine, E. C., G. Thomas, A. L. Boulesteix, A. S. Khashan, and L. C. Kenny. 2017. “Critical Review of Reporting of the Data Analysis Step in Metabolomics.” Metabolomics 14 (1): 7. https://doi.org/10.1007/s11306-017-1299-3.
Creek, Darren J., Andris Jankevics, Karl E. V. Burgess, Rainer Breitling, and Michael P. Barrett. 2012. “IDEOM: An Excel Interface for Analysis of LC–MS-based Metabolomics Data.” Bioinformatics 28 (7): 1048–49. https://doi.org/10.1093/bioinformatics/bts069.
Dagan, Shai, Dana Marder, Nitzan Tzanani, Eyal Drug, Hagit Prihed, and Lilach Yishai-Aviram. 2023. “Evaluation of Matrix Complexity in Nontargeted Analysis of Small-Molecule Toxicants by Liquid Chromatography–High-Resolution Mass Spectrometry.” Analytical Chemistry 95 (20): 7924–32. https://doi.org/10.1021/acs.analchem.3c00413.
Daly, Rónán, Simon Rogers, Joe Wandy, Andris Jankevics, Karl E. V. Burgess, and Rainer Breitling. 2014. “MetAssign: Probabilistic Annotation of Metabolites from LC–MS Data Using a Bayesian Clustering Approach.” Bioinformatics 30 (19): 2764–71. https://doi.org/10.1093/bioinformatics/btu370.
de Jonge, Niek F., Joris J. R. Louwen, Elena Chekmeneva, Stephane Camuzeaux, Femke J. Vermeir, Robert S. Jansen, Florian Huber, and Justin J. J. van der Hooft. 2023. “MS2Query: Reliable and Scalable MS2 Mass Spectra-Based Analogue Search.” Nature Communications 14 (1): 1752. https://doi.org/10.1038/s41467-023-37446-4.
De Livera, Alysha M., Daniel A. Dias, David De Souza, Thusitha Rupasinghe, James Pyke, Dedreia Tull, Ute Roessner, Malcolm McConville, and Terence P. Speed. 2012. “Normalizing and Integrating Metabolomics Data.” Analytical Chemistry 84 (24): 10768–76. https://doi.org/10.1021/ac302748b.
Deda, Olga, Anastasia Chrysovalantou Chatziioannou, Stella Fasoula, Dimitris Palachanis, Nicolaos Raikos, Georgios A. Theodoridis, and Helen G. Gika. 2017. “Sample Preparation Optimization in Fecal Metabolic Profiling.” Journal of Chromatography B, Advances in mass spectrometry-based applications, 1047 (March): 115–23. https://doi.org/10.1016/j.jchromb.2016.06.047.
DeFelice, Brian C., Sajjan Singh Mehta, Stephanie Samra, Tomáš Čajka, Benjamin Wancewicz, Johannes F. Fahrmann, and Oliver Fiehn. 2017. “Mass Spectral Feature List Optimizer (MS-FLO): A Tool To Minimize False Positive Peak Reports in Untargeted Liquid Chromatography–Mass Spectroscopy (LC-MS) Data Processing.” Analytical Chemistry 89 (6): 3250–55. https://doi.org/10.1021/acs.analchem.6b04372.
Delabriere, Alexis, Philipp Warmer, Vincenth Brennsteiner, and Nicola Zamboni. 2021. “SLAW: A Scalable and Self-Optimizing Processing Workflow for Untargeted LC-MS.” Analytical Chemistry 93 (45): 15024–32. https://doi.org/10.1021/acs.analchem.1c02687.
Dietrich, Christian, Arne Wick, and Thomas A. Ternes. 2022. “Open-Source Feature Detection for Non-Target LC–MS Analytics.” Rapid Communications in Mass Spectrometry 36 (2): e9206. https://doi.org/10.1002/rcm.9206.
Ding, Xian, Fen Yang, Yanhua Chen, Jing Xu, Jiuming He, Ruiping Zhang, and Zeper Abliz. 2022. “Norm ISWSVR: A Data Integration and Normalization Approach for Large-Scale Metabolomics.” Analytical Chemistry 94 (21): 7500–7509. https://doi.org/10.1021/acs.analchem.1c05502.
Djoumbou Feunang, Yannick, Roman Eisner, Craig Knox, Leonid Chepelev, Janna Hastings, Gareth Owen, Eoin Fahy, et al. 2016. “ClassyFire: Automated Chemical Classification with a Comprehensive, Computable Taxonomy.” Journal of Cheminformatics 8 (1): 61. https://doi.org/10.1186/s13321-016-0174-y.
Dodds, James N., Lingjue Wang, Gary J. Patti, and Erin S. Baker. 2022. “Combining Isotopologue Workflows and Simultaneous Multidimensional Separations to Detect, Identify, and Validate Metabolites in Untargeted Analyses.” Analytical Chemistry 94 (5): 2527–35. https://doi.org/10.1021/acs.analchem.1c04430.
Domingo-Almenara, Xavier, Jesus Brezmes, Maria Vinaixa, Sara Samino, Noelia Ramirez, Marta Ramon-Krauel, Carles Lerin, et al. 2016. “eRah: A Computational Tool Integrating Spectral Deconvolution and Alignment with Quantification and Identification of Metabolites in GC/MS-Based Metabolomics.” Analytical Chemistry 88 (19): 9821–29. https://doi.org/10.1021/acs.analchem.6b02927.
Domingo-Almenara, Xavier, J. Rafael Montenegro-Burke, H. Paul Benton, and Gary Siuzdak. 2018. “Annotation: A Computational Solution for Streamlining Metabolomics Analysis.” Analytical Chemistry 90 (1): 480–89. https://doi.org/10.1021/acs.analchem.7b03929.
Domingo-Almenara, Xavier, J. Rafael Montenegro-Burke, Julijana Ivanisevic, Aurelien Thomas, Jonathan Sidibé, Tony Teav, Carlos Guijas, et al. 2018. “XCMS-MRM and METLIN-MRM: A Cloud Library and Public Resource for Targeted Analysis of Small Molecules.” Nature Methods 15 (9): 681–84. https://doi.org/10.1038/s41592-018-0110-3.
Domingo-Almenara, Xavier, and Gary Siuzdak. 2020. “Metabolomics Data Processing Using XCMS.” In Computational Methods and Data Analysis for Metabolomics, edited by Shuzhao Li, 11–24. Methods in Molecular Biology. New York, NY: Springer US. https://doi.org/10.1007/978-1-0716-0239-3_2.
Doppler, Maria, Bernhard Kluger, Christoph Bueschl, Christina Schneider, Rudolf Krska, Sylvie Delcambre, Karsten Hiller, Marc Lemmens, and Rainer Schuhmacher. 2016. “Stable Isotope-Assisted Evaluation of Different Extraction Solvents for Untargeted Metabolomics of Plants.” International Journal of Molecular Sciences 17 (7). https://doi.org/10.3390/ijms17071017.
Dos Santos, Emile Kelly Porto, and Gisele André Baptista Canuto. 2023. “Optimizing XCMS Parameters for GC-MS Metabolomics Data Processing: A Case Study.” Metabolomics: Official Journal of the Metabolomic Society 19 (4): 26. https://doi.org/10.1007/s11306-023-01992-1.
Dryden, Michael D. M., Ryan Fobel, Christian Fobel, and Aaron R. Wheeler. 2017. “Upon the Shoulders of Giants: Open-Source Hardware and Software in Analytical Chemistry.” Analytical Chemistry 89 (8): 4330–38. https://doi.org/10.1021/acs.analchem.7b00485.
Du, Xinsong, Juan J. Aristizabal-Henao, Timothy J. Garrett, Mathias Brochhausen, William R. Hogan, and Dominick J. Lemas. 2022. “A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research.” Metabolites 12 (1): 87. https://doi.org/10.3390/metabo12010087.
Du, Xiuxia, and Steven H Zeisel. 2013. “SPECTRAL DECONVOLUTION FOR GAS CHROMATOGRAPHY MASS SPECTROMETRY-BASED METABOLOMICS: CURRENT STATUS AND FUTURE PERSPECTIVES.” Computational and Structural Biotechnology Journal 4 (5): 1–10. https://doi.org/10.5936/csbj.201301013.
Dudzik, Danuta, Cecilia Barbas-Bernardos, Antonia García, and Coral Barbas. 2018. “Quality Assurance Procedures for Mass Spectrometry Untargeted Metabolomics. A Review.” Journal of Pharmaceutical and Biomedical Analysis, Review issue 2017, 147 (January): 149–73. https://doi.org/10.1016/j.jpba.2017.07.044.
Dührkop, Kai, Markus Fleischauer, Marcus Ludwig, Alexander A. Aksenov, Alexey V. Melnik, Marvin Meusel, Pieter C. Dorrestein, Juho Rousu, and Sebastian Böcker. 2019. “SIRIUS 4: A Rapid Tool for Turning Tandem Mass Spectra into Metabolite Structure Information.” Nature Methods 16 (4): 299–302. https://doi.org/10.1038/s41592-019-0344-8.
Dührkop, Kai, Louis-Félix Nothias, Markus Fleischauer, Raphael Reher, Marcus Ludwig, Martin A. Hoffmann, Daniel Petras, et al. 2020. “Systematic Classification of Unknown Metabolites Using High-Resolution Fragmentation Mass Spectra.” Nature Biotechnology, November, 1–10. https://doi.org/10.1038/s41587-020-0740-8.
Dunn, Warwick B, Ian D Wilson, Andrew W Nicholls, and David Broadhurst. 2012. “The Importance of Experimental Design and QC Samples in Large-Scale and MS-driven Untargeted Metabolomic Studies of Humans.” Bioanalysis 4 (18): 2249–64. https://doi.org/10.4155/bio.12.204.
Dyar, Kenneth A., Dominik Lutter, Anna Artati, Nicholas J. Ceglia, Yu Liu, Danny Armenta, Martin Jastroch, et al. 2018. “Atlas of Circadian Metabolism Reveals System-wide Coordination and Communication Between Clocks.” Cell 174 (6): 1571–1585.e11. https://doi.org/10.1016/j.cell.2018.08.042.
Edmands, William M. B., Dinesh K. Barupal, and Augustin Scalbert. 2015. “MetMSLine: An Automated and Fully Integrated Pipeline for Rapid Processing of High-Resolution LC–MS Metabolomic Datasets.” Bioinformatics 31 (5): 788–90. https://doi.org/10.1093/bioinformatics/btu705.
Edmands, William M. B., Josie Hayes, and Stephen M. Rappaport. 2018. “SimExTargId: A Comprehensive Package for Real-Time LC-MS Data Acquisition and Analysis.” Bioinformatics 34 (20): 3589–90. https://doi.org/10.1093/bioinformatics/bty218.
Edmands, William M. B., Lauren Petrick, Dinesh K. Barupal, Augustin Scalbert, Mark J. Wilson, Jeffrey K. Wickliffe, and Stephen M. Rappaport. 2017. “compMS2Miner: An Automatable Metabolite Identification, Visualization, and Data-Sharing R Package for High-Resolution LC–MS Data Sets.” Analytical Chemistry 89 (7): 3919–28. https://doi.org/10.1021/acs.analchem.6b02394.
Eilertz, Daniel, Michael Mitterer, and Joerg M. Buescher. 2022. “automRm: An R Package for Fully Automatic LC-QQQ-MS Data Preprocessing Powered by Machine Learning.” Analytical Chemistry 94 (16): 6163–71. https://doi.org/10.1021/acs.analchem.1c05224.
El Abiead, Yasin, Maximilian Milford, Harald Schoeny, Mate Rusz, Reza M. Salek, and Gunda Koellensperger. 2022. “Power of mzRAPP-Based Performance Assessments in MS1-Based Nontargeted Feature Detection.” Analytical Chemistry 94 (24): 8588–95. https://doi.org/10.1021/acs.analchem.1c05270.
Engler Hart, Chloe, Tobias Kind, Pieter C. Dorrestein, David Healey, and Daniel Domingo-Fernández. 2024. “Weighting Low-Intensity MS/MS Ions and m/z Frequency for Spectral Library Annotation.” Journal of the American Society for Mass Spectrometry 35 (2): 266–74. https://doi.org/10.1021/jasms.3c00353.
Fenaille, François, Pierre Barbier Saint-Hilaire, Kathleen Rousseau, and Christophe Junot. 2017. “Data Acquisition Workflows in Liquid Chromatography Coupled to High Resolution Mass Spectrometry-Based Metabolomics: Where Do We Stand?” Journal of Chromatography A 1526 (Supplement C): 1–12. https://doi.org/10.1016/j.chroma.2017.10.043.
Fernández-Albert, Francesc, Rafael Llorach, Cristina Andrés-Lacueva, and Alexandre Perera. 2014. “An R Package to Analyse LC/MS Metabolomic Data: MAIT (Metabolite Automatic Identification Toolkit).” Bioinformatics 30 (13): 1937–39. https://doi.org/10.1093/bioinformatics/btu136.
Fessenden, Marissa. 2016. “Metabolomics: Small Molecules, Single Cells.” Nature 540 (7631): 153–55. https://doi.org/10.1038/540153a.
Fiehn, Oliver. 2002. “Metabolomics – the Link Between Genotypes and Phenotypes.” Plant Molecular Biology 48 (1): 155–71. https://doi.org/10.1023/A:1013713905833.
Flasch, Mira, Veronika Fitz, Evelyn Rampler, Chibundu N. Ezekiel, Gunda Koellensperger, and Benedikt Warth. 2022. “Integrated Exposomics/Metabolomics for Rapid Exposure and Effect Analyses.” JACS Au 2 (11): 2548–60. https://doi.org/10.1021/jacsau.2c00433.
Forsberg, Erica M., Tao Huan, Duane Rinehart, H. Paul Benton, Benedikt Warth, Brian Hilmers, and Gary Siuzdak. 2018. “Data Processing, Multi-Omic Pathway Mapping, and Metabolite Activity Analysis Using XCMS Online.” Nature Protocols 13 (4): 633–51. https://doi.org/10.1038/nprot.2017.151.
Franceschi, Pietro, Domenico Masuero, Urska Vrhovsek, Fulvio Mattivi, and Ron Wehrens. 2012. “A Benchmark Spike-in Data Set for Biomarker Identification in Metabolomics.” Journal of Chemometrics 26 (1-2): 16–24. https://doi.org/10.1002/cem.1420.
Fu, Hai-Yan, Ou Hu, Yue-Ming Zhang, Li Zhang, Jing-Jing Song, Peang Lu, Qing-Xia Zheng, et al. 2017. “Mass-Spectra-Based Peak Alignment for Automatic Nontargeted Metabolic Profiling Analysis for Biomarker Screening in Plant Samples.” Journal of Chromatography A 1513 (Supplement C): 201–9. https://doi.org/10.1016/j.chroma.2017.07.044.
Fu, Jianbo, Ying Zhang, Yunxia Wang, Hongning Zhang, Jin Liu, Jing Tang, Qingxia Yang, et al. 2021. “Optimization of Metabolomic Data Processing Using NOREVA.” Nature Protocols, December, 1–23. https://doi.org/10.1038/s41596-021-00636-9.
Gadara, Darshak, Katerina Coufalikova, Juraj Bosak, David Smajs, and Zdenek Spacil. 2021. “Systematic Feature Filtering in Exploratory Metabolomics: Application Toward Biomarker Discovery.” Analytical Chemistry 93 (26): 9103–10. https://doi.org/10.1021/acs.analchem.1c00816.
Gerlich, Michael, and Steffen Neumann. 2013. “MetFusion: Integration of Compound Identification Strategies.” Journal of Mass Spectrometry 48 (3): 291–98. https://doi.org/10.1002/jms.3123.
Ghaste, Manoj, Robert Mistrik, and Vladimir Shulaev. 2016. “Applications of Fourier Transform Ion Cyclotron Resonance (FT-ICR) and Orbitrap Based High Resolution Mass Spectrometry in Metabolomics and Lipidomics.” International Journal of Molecular Sciences 17 (6). https://doi.org/10.3390/ijms17060816.
Ghosson, Hikmat, Yann Guitton, Amani Ben Jrad, Chandrashekhar Patil, Delphine Raviglione, Marie-Virginie Salvia, and Cédric Bertrand. 2021. “Electrospray Ionization and Heterogeneous Matrix Effects in Liquid Chromatography/Mass Spectrometry Based Meta-Metabolomics: A Biomarker or a Suppressed Ion?” Rapid Communications in Mass Spectrometry 35 (2): e8977. https://doi.org/10.1002/rcm.8977.
Giacomoni, Franck, Gildas Le Corguillé, Misharl Monsoor, Marion Landi, Pierre Pericard, Mélanie Pétéra, Christophe Duperier, et al. 2015. “Workflow4Metabolomics: A Collaborative Research Infrastructure for Computational Metabolomics.” Bioinformatics 31 (9): 1493–95. https://doi.org/10.1093/bioinformatics/btu813.
Giebelhaus, Ryland T., Michael D. Sorochan Armstrong, A. Paulina de la Mata, and James J. Harynuk. 2022. “Untargeted Region of Interest Selection for Gas Chromatography – Mass Spectrometry Data Using a Pseudo F-ratio Moving Window.” Journal of Chromatography A 1682 (October): 463499. https://doi.org/10.1016/j.chroma.2022.463499.
Gika, Helen G., Georgios A. Theodoridis, Robert S. Plumb, and Ian D. Wilson. 2014. “Current Practice of Liquid Chromatography–Mass Spectrometry in Metabolomics and Metabonomics.” Journal of Pharmaceutical and Biomedical Analysis, Review Papers on Pharmaceutical and Biomedical Analysis 2013, 87 (January): 12–25. https://doi.org/10.1016/j.jpba.2013.06.032.
Gil, Andres, David Siegel, Hjalmar Permentier, Dirk-Jan Reijngoud, Frank Dekker, and Rainer Bischoff. 2015. “Stability of Energy Metabolites—An Often Overlooked Issue in Metabolomics Studies: A Review.” ELECTROPHORESIS 36 (18): 2156–69. https://doi.org/10.1002/elps.201500031.
Giné, Roger, Jordi Capellades, Josep M. Badia, Dennis Vughs, Michaela Schwaiger-Haber, Theodore Alexandrov, Maria Vinaixa, Andrea M. Brunner, Gary J. Patti, and Oscar Yanes. 2021. “HERMES: A Molecular-Formula-Oriented Method to Target the Metabolome.” Nature Methods 18 (11): 1370–76. https://doi.org/10.1038/s41592-021-01307-z.
Gloaguen, Yoann, Jennifer A. Kirwan, and Dieter Beule. 2022. “Deep Learning-Assisted Peak Curation for Large-Scale LC-MS Metabolomics.” Analytical Chemistry 94 (12): 4930–37. https://doi.org/10.1021/acs.analchem.1c02220.
Goldansaz, Seyed Ali, An Chi Guo, Tanvir Sajed, Michael A. Steele, Graham S. Plastow, and David S. Wishart. 2017. “Livestock Metabolomics and the Livestock Metabolome: A Systematic Review.” PLOS ONE 12 (5): e0177675. https://doi.org/10.1371/journal.pone.0177675.
González, Oskar, Anne-Charlotte Dubbelman, and Thomas Hankemeier. 2022. “Postcolumn Infusion as a Quality Control Tool for LC-MS-Based Analysis.” Postcolumn Infusion as a Quality Control Tool for LC-MS-Based Analysis, April. https://doi.org/10.1021/jasms.2c00022.
González-Domínguez, Álvaro, Núria Estanyol-Torres, Carl Brunius, Rikard Landberg, and Raúl González-Domínguez. 2024. “QComics: Recommendations and Guidelines for Robust, Easily Implementable and Reportable Quality Control of Metabolomics Data.” Analytical Chemistry 96 (3): 1064–72. https://doi.org/10.1021/acs.analchem.3c03660.
González-Riano, Carolina, Danuta Dudzik, Antonia Garcia, Alberto Gil-de-la-Fuente, Ana Gradillas, Joanna Godzien, Ángeles López-Gonzálvez, et al. 2020. “Recent Developments Along the Analytical Process for Metabolomics Workflows.” Analytical Chemistry 92 (1): 203–26. https://doi.org/10.1021/acs.analchem.9b04553.
Goracci, Laura, Paolo Tiberi, Stefano Di Bona, Stefano Bonciarelli, Giovanna Ilaria Passeri, Marta Piroddi, Simone Moretti, Claudia Volpi, Ismael Zamora, and Gabriele Cruciani. 2024. “MARS: A Multipurpose Software for Untargeted LC–MS-Based Metabolomics and Exposomics.” Analytical Chemistry, January. https://doi.org/10.1021/acs.analchem.3c03620.
Graça, Gonçalo, Yuheng Cai, Chung-Ho E. Lau, Panagiotis A. Vorkas, Matthew R. Lewis, Elizabeth J. Want, David Herrington, and Timothy M. D. Ebbels. 2022. “Automated Annotation of Untargeted All-Ion Fragmentation LC–MS Metabolomics Data with MetaboAnnotatoR.” Analytical Chemistry 94 (8): 3446–55. https://doi.org/10.1021/acs.analchem.1c03032.
Griffiths, William J., Therese Koal, Yuqin Wang, Matthias Kohl, David P. Enot, and Hans-Peter Deigner. 2010. “Targeted Metabolomics for Biomarker Discovery.” Angewandte Chemie International Edition 49 (32): 5426–45. https://doi.org/10.1002/anie.200905579.
Gromski, Piotr S., Howbeer Muhamadali, David I. Ellis, Yun Xu, Elon Correa, Michael L. Turner, and Royston Goodacre. 2015. “A Tutorial Review: Metabolomics and Partial Least Squares-Discriminant Analysis – a Marriage of Convenience or a Shotgun Wedding.” Analytica Chimica Acta 879 (June): 10–23. https://doi.org/10.1016/j.aca.2015.02.012.
Groves, Ryan A., Carly C. Y. Chan, Spencer D. Wildman, Daniel B. Gregson, Thomas Rydzak, and Ian A. Lewis. 2023. “Rapid LC–MS Assay for Targeted Metabolite Quantification by Serial Injection into Isocratic Gradients.” Analytical and Bioanalytical Chemistry 415 (2): 269–76. https://doi.org/10.1007/s00216-022-04384-x.
Gugisch, Ralf, Adalbert Kerber, Axel Kohnert, Reinhard Laue, Markus Meringer, Christoph Rücker, and Alfred Wassermann. 2015. “Chapter 6 - MOLGEN 5.0, A Molecular Structure Generator.” In Advances in Mathematical Chemistry and Applications, edited by Subhash C. Basak, Guillermo Restrepo, and José L. Villaveces, 113–38. Bentham Science Publishers. https://doi.org/10.1016/B978-1-68108-198-4.50006-0.
Guha, Rajarshi. 2007. “Chemical Informatics Functionality in R.” Journal of Statistical Software 18 (1): 1–16. https://doi.org/10.18637/jss.v018.i05.
Guijas, Carlos, J. Rafael Montenegro-Burke, Xavier Domingo-Almenara, Amelia Palermo, Benedikt Warth, Gerrit Hermann, Gunda Koellensperger, et al. 2018. “METLIN: A Technology Platform for Identifying Knowns and Unknowns.” Analytical Chemistry 90 (5): 3156–64. https://doi.org/10.1021/acs.analchem.7b04424.
Guo, Hao, Kebing Xue, Haiming Sun, Weihao Jiang, and Shiliang Pu. 2023. “Contrastive Learning-Based Embedder for the Representation of Tandem Mass Spectra.” Analytical Chemistry, May. https://doi.org/10.1021/acs.analchem.3c00260.
Guo, Jian, and Tao Huan. 2020. “Comparison of Full-Scan, Data-Dependent, and Data-Independent Acquisition Modes in Liquid Chromatography–Mass Spectrometry Based Untargeted Metabolomics.” Analytical Chemistry 92 (12): 8072–80. https://doi.org/10.1021/acs.analchem.9b05135.
Guo, Jian, Sam Shen, and Tao Huan. 2022. “Paramounter: Direct Measurement of Universal Parameters To Process Metabolomics Data in a ‘White Box’.” Analytical Chemistry, March. https://doi.org/10.1021/acs.analchem.1c04758.
Guo, Jian, Sam Shen, Shipei Xing, Huaxu Yu, and Tao Huan. 2021. “ISFrag: De Novo Recognition of In-Source Fragments for Liquid Chromatography–Mass Spectrometry Data.” Analytical Chemistry, July. https://doi.org/10.1021/acs.analchem.1c01644.
Habra, Hani, Maureen Kachman, Kevin Bullock, Clary Clish, Charles R. Evans, and Alla Karnovsky. 2021. “metabCombiner: Paired Untargeted LC-HRMS Metabolomics Feature Matching and Concatenation of Disparately Acquired Data Sets.” Analytical Chemistry 93 (12): 5028–36. https://doi.org/10.1021/acs.analchem.0c03693.
Hansen, Rebecca L., and Young Jin Lee. 2018. “High-Spatial Resolution Mass Spectrometry Imaging: Toward Single Cell Metabolomics in Plant Tissues.” The Chemical Record 18 (1): 65–77. https://doi.org/10.1002/tcr.201700027.
Hao, Jun-Di, Yao-Yu Chen, Yan-Zhen Wang, Na An, Pei-Rong Bai, Quan-Fei Zhu, and Yu-Qi Feng. 2023. “Novel Peak Shift Correction Method Based on the Retention Index for Peak Alignment in Untargeted Metabolomics.” Analytical Chemistry 95 (35): 13330–37. https://doi.org/10.1021/acs.analchem.3c02583.
Harrieder, Eva-Maria, Fleming Kretschmer, Sebastian Böcker, and Michael Witting. 2022. “Current State-of-the-Art of Separation Methods Used in LC-MS Based Metabolomics and Lipidomics.” Journal of Chromatography B 1188 (January): 123069. https://doi.org/10.1016/j.jchromb.2021.123069.
Harwood, Thomas V., Daniel G. C. Treen, Mingxun Wang, Wibe de Jong, Trent R. Northen, and Benjamin P. Bowen. 2023. “BLINK Enables Ultrafast Tandem Mass Spectrometry Cosine Similarity Scoring.” Scientific Reports 13 (1): 13462. https://doi.org/10.1038/s41598-023-40496-9.
Haug, Kenneth, Reza M Salek, and Christoph Steinbeck. 2017. “Global Open Data Management in Metabolomics.” Current Opinion in Chemical Biology, Omics, 36 (February): 58–63. https://doi.org/10.1016/j.cbpa.2016.12.024.
Helmus, Rick, Thomas L. ter Laak, Annemarie P. van Wezel, Pim de Voogt, and Emma L. Schymanski. 2021. “patRoon: Open Source Software Platform for Environmental Mass Spectrometry Based Non-Target Screening.” Journal of Cheminformatics 13 (1): 1. https://doi.org/10.1186/s13321-020-00477-w.
Hernandes, Vinicius Veri, Coral Barbas, and Danuta Dudzik. 2017. “A Review of Blood Sample Handling and Pre-Processing for Metabolomics Studies.” ELECTROPHORESIS 38 (18): 2232–41. https://doi.org/10.1002/elps.201700086.
Hiller, Karsten, Jasper Hangebrauk, Christian Jäger, Jana Spura, Kerstin Schreiber, and Dietmar Schomburg. 2009. “MetaboliteDetector: Comprehensive Analysis Tool for Targeted and Nontargeted GC/MS Based Metabolome Analysis.” Analytical Chemistry 81 (9): 3429–39. https://doi.org/10.1021/ac802689c.
Hites, Ronald A. 2019. “Correcting for Censored Environmental Measurements.” Environmental Science & Technology, September. https://doi.org/10.1021/acs.est.9b05042.
Hites, Ronald A., and Karl J. Jobst. 2018. “Is Nontargeted Screening Reproducible?” Environmental Science & Technology 52 (21): 11975–76. https://doi.org/10.1021/acs.est.8b05671.
Houriet, Joelle, Warren S. Vidar, Preston K. Manwill, Daniel A. Todd, and Nadja B. Cech. 2022. “How Low Can You Go? Selecting Intensity Thresholds for Untargeted Metabolomics Data Preprocessing.” Analytical Chemistry 94 (51): 17964–71. https://doi.org/10.1021/acs.analchem.2c04088.
Hu, Xin, Douglas I. Walker, Yongliang Liang, Matthew Ryan Smith, Michael L. Orr, Brian D. Juran, Chunyu Ma, et al. 2021. “A Scalable Workflow to Characterize the Human Exposome.” Nature Communications 12 (1): 5575. https://doi.org/10.1038/s41467-021-25840-9.
Hu, Yaxi, Betty Cai, and Tao Huan. 2019. “Enhancing Metabolome Coverage in Data-Dependent LC–MS/MS Analysis Through an Integrated Feature Extraction Strategy.” Analytical Chemistry 91 (22): 14433–41. https://doi.org/10.1021/acs.analchem.9b02980.
Huan, Tao, Erica M. Forsberg, Duane Rinehart, Caroline H. Johnson, Julijana Ivanisevic, H. Paul Benton, Mingliang Fang, et al. 2017. “Systems Biology Guided by XCMS Online Metabolomics.” Nature Methods 14 (5): 461–62. https://doi.org/10.1038/nmeth.4260.
Huang, Danning, Marcos Bouza, David A. Gaul, Franklin E. Leach, I. Jonathan Amster, Frank C. Schroeder, Arthur S. Edison, and Facundo M. Fernández. 2021. “Comparison of High-Resolution Fourier Transform Mass Spectrometry Platforms for Putative Metabolite Annotation.” Comparison of High-Resolution Fourier Transform Mass Spectrometry Platforms for Putative Metabolite Annotation, August. https://doi.org/10.1021/acs.analchem.1c02224.
Huber, Florian, Stefan Verhoeven, Christiaan Meijer, Hanno Spreeuw, Efraín Manuel Villanueva Castilla, Cunliang Geng, Justin J. j van der Hooft, et al. 2020. “Matchms - Processing and Similarity Evaluation of Mass Spectrometry Data.” Journal of Open Source Software 5 (52): 2411. https://doi.org/10.21105/joss.02411.
Hufsky, Franziska, Kerstin Scheubert, and Sebastian Böcker. 2014. “Computational Mass Spectrometry for Small-Molecule Fragmentation.” TrAC Trends in Analytical Chemistry 53 (January): 41–48. https://doi.org/10.1016/j.trac.2013.09.008.
Ibáñez, Clara, Lamia Mouhid, Guillermo Reglero, and Ana Ramírez de Molina. 2017. “Lipidomics Insights in Health and Nutritional Intervention Studies.” Journal of Agricultural and Food Chemistry 65 (36): 7827–42. https://doi.org/10.1021/acs.jafc.7b02643.
Jacyna, Julia, Marta Kordalewska, and Michał J. Markuszewski. 2019. “Design of Experiments in Metabolomics-Related Studies: An Overview.” Journal of Pharmaceutical and Biomedical Analysis 164 (February): 598–606. https://doi.org/10.1016/j.jpba.2018.11.027.
Jaeger, Carsten, Friederike Hoffmann, Clemens A. Schmitt, and Jan Lisec. 2016. “Automated Annotation and Evaluation of In-Source Mass Spectra in GC/Atmospheric Pressure Chemical Ionization-MS-Based Metabolomics.” Analytical Chemistry 88 (19): 9386–90. https://doi.org/10.1021/acs.analchem.6b02743.
Jalili, Vahid, Enis Afgan, Qiang Gu, Dave Clements, Daniel Blankenberg, Jeremy Goecks, James Taylor, and Anton Nekrutenko. 2020. “The Galaxy Platform for Accessible, Reproducible and Collaborative Biomedical Analyses: 2020 Update.” Nucleic Acids Research 48 (W1): W395–402. https://doi.org/10.1093/nar/gkaa434.
Jang, Cholsoon, Li Chen, and Joshua D. Rabinowitz. 2018. “Metabolomics and Isotope Tracing.” Cell 173 (4): 822–37. https://doi.org/10.1016/j.cell.2018.03.055.
Jones, Dean P., Youngja Park, and Thomas R. Ziegler. 2012. “Nutritional Metabolomics: Progress in Addressing Complexity in Diet and Health.” Annual Review of Nutrition 32 (1): 183–202. https://doi.org/10.1146/annurev-nutr-072610-145159.
Jorge, Tiago F., Ana T. Mata, and Carla António. 2016. “Mass Spectrometry as a Quantitative Tool in Plant Metabolomics.” Phil. Trans. R. Soc. A 374 (2079): 20150370. https://doi.org/10.1098/rsta.2015.0370.
Jr, Stephen Salerno, Mahya Mehrmohamadi, Maria V. Liberti, Muting Wan, Martin T. Wells, James G. Booth, and Jason W. Locasale. 2017. “RRmix: A Method for Simultaneous Batch Effect Correction and Analysis of Metabolomics Data in the Absence of Internal Standards.” PLOS ONE 12 (6): e0179530. https://doi.org/10.1371/journal.pone.0179530.
Ju, Ran, Xinyu Liu, Fujian Zheng, Xinjie Zhao, Xin Lu, Xiaohui Lin, Zhongda Zeng, and Guowang Xu. 2020. “A Graph Density-Based Strategy for Features Fusion from Different Peak Extract Software to Achieve More Metabolites in Metabolic Profiling from High-Resolution Mass Spectrometry.” Analytica Chimica Acta 1139 (December): 8–14. https://doi.org/10.1016/j.aca.2020.09.029.
Kachman, Maureen, Hani Habra, William Duren, Janis Wigginton, Peter Sajjakulnukit, George Michailidis, Charles Burant, and Alla Karnovsky. 2020. “Deep Annotation of Untargeted LC-MS Metabolomics Data with Binner.” Bioinformatics 36 (6): 1801–6. https://doi.org/10.1093/bioinformatics/btz798.
Kapoore, Rahul Vijay, and Seetharaman Vaidyanathan. 2016. “Towards Quantitative Mass Spectrometry-Based Metabolomics in Microbial and Mammalian Systems.” Phil. Trans. R. Soc. A 374 (2079): 20150363. https://doi.org/10.1098/rsta.2015.0363.
Karpievitch, Yuliya V., Sonja B. Nikolic, Richard Wilson, James E. Sharman, and Lindsay M. Edwards. 2014. “Metabolomics Data Normalization with EigenMS.” PLOS ONE 9 (12): e116221. https://doi.org/10.1371/journal.pone.0116221.
Kennedy, Adam D., Bryan M. Wittmann, Anne M. Evans, Luke A. D. Miller, Douglas R. Toal, Shaun Lonergan, Sarah H. Elsea, and Kirk L. Pappan. 2018. “Metabolomics in the Clinic: A Review of the Shared and Unique Features of Untargeted Metabolomics for Clinical Research and Clinical Testing.” Journal of Mass Spectrometry 53 (11): 1143–54. https://doi.org/10.1002/jms.4292.
Keshet, Uri, Tobias Kind, Xinchen Lu, Sarita Devi, and Oliver Fiehn. 2022. “Acyl-CoA Identification in Mouse Liver Samples Using the In Silico CoA-Blast Tandem Mass Spectral Library.” Analytical Chemistry 94 (6): 2732–39. https://doi.org/10.1021/acs.analchem.1c03272.
Kew, William, John W. T. Blackburn, David J. Clarke, and Dušan Uhrín. 2017. “Interactive van Krevelen Diagrams – Advanced Visualisation of Mass Spectrometry Data of Complex Mixtures.” Rapid Communications in Mass Spectrometry 31 (7): 658–62. https://doi.org/10.1002/rcm.7823.
Kim, Jungyeon, Joong Kyong Ahn, Yu Eun Cheong, Sung-Joon Lee, Hoon-Suk Cha, and Kyoung Heon Kim. 2020. “Systematic Re-Evaluation of the Long-Used Standard Protocol of Urease-Dependent Metabolome Sample Preparation.” PloS One 15 (3): e0230072. https://doi.org/10.1371/journal.pone.0230072.
Kim, Taiyun, Owen Tang, Stephen T. Vernon, Katharine A. Kott, Yen Chin Koay, John Park, David E. James, et al. 2021. “A Hierarchical Approach to Removal of Unwanted Variation for Large-Scale Metabolomics Data.” Nature Communications 12 (1): 4992. https://doi.org/10.1038/s41467-021-25210-5.
Kind, Tobias, and Oliver Fiehn. 2007. “Seven Golden Rules for Heuristic Filtering of Molecular Formulas Obtained by Accurate Mass Spectrometry.” BMC Bioinformatics 8 (1): 105. https://doi.org/10.1186/1471-2105-8-105.
Kind, Tobias, Hiroshi Tsugawa, Tomas Cajka, Yan Ma, Zijuan Lai, Sajjan S. Mehta, Gert Wohlgemuth, et al. 2018. “Identification of Small Molecules Using Accurate Mass MS/MS Search.” Mass Spectrometry Reviews 37 (4): 513–32. https://doi.org/10.1002/mas.21535.
Koelmel, Jeremy P., Nicholas M. Kroeger, Candice Z. Ulmer, John A. Bowden, Rainey E. Patterson, Jason A. Cochran, Christopher W. W. Beecher, Timothy J. Garrett, and Richard A. Yost. 2017. “LipidMatch: An Automated Workflow for Rule-Based Lipid Identification Using Untargeted High-Resolution Tandem Mass Spectrometry Data.” BMC Bioinformatics 18 (July): 331. https://doi.org/10.1186/s12859-017-1744-3.
Kong, Fanzhou, Uri Keshet, Tong Shen, Elys Rodriguez, and Oliver Fiehn. 2023. “LibGen: Generating High Quality Spectral Libraries of Natural Products for EAD-, UVPD-, and HCD-High Resolution Mass Spectrometers.” Analytical Chemistry, November. https://doi.org/10.1021/acs.analchem.3c02263.
Kouřil, Štěpán, Julie de Sousa, Jan Václavík, David Friedecký, and Tomáš Adam. 2020. “CROP: Correlation-Based Reduction of Feature Multiplicities in Untargeted Metabolomic Data.” Bioinformatics 36 (9): 2941–42. https://doi.org/10.1093/bioinformatics/btaa012.
Kuhl, Carsten, Ralf Tautenhahn, Christoph Böttcher, Tony R. Larson, and Steffen Neumann. 2012. “CAMERA: An Integrated Strategy for Compound Spectra Extraction and Annotation of Liquid Chromatography/Mass Spectrometry Data Sets.” Analytical Chemistry 84 (1): 283–89. https://doi.org/10.1021/ac202450g.
Kuligowski, Julia, Ángel Sánchez-Illana, Daniel Sanjuán-Herráez, Máximo Vento, and Guillermo Quintás. 2015. “Intra-Batch Effect Correction in Liquid Chromatography-Mass Spectrometry Using Quality Control Samples and Support Vector Regression (QC-SVRC).” Analyst 140 (22): 7810–17. https://doi.org/10.1039/C5AN01638J.
Kusonmano, Kanthida, Wanwipa Vongsangnak, and Pramote Chumnanpuen. 2016. “Informatics for Metabolomics.” In Translational Biomedical Informatics, 91–115. Advances in Experimental Medicine and Biology. Springer, Singapore. https://doi.org/10.1007/978-981-10-1503-8_5.
Lai, Zijuan, Hiroshi Tsugawa, Gert Wohlgemuth, Sajjan Mehta, Matthew Mueller, Yuxuan Zheng, Atsushi Ogiwara, et al. 2018. “Identifying Metabolites by Integrating Metabolome Databases with Mass Spectrometry Cheminformatics.” Nature Methods 15 (1): 53–56. https://doi.org/10.1038/nmeth.4512.
Lakhani, Chirag M., Braden T. Tierney, Arjun K. Manrai, Jian Yang, Peter M. Visscher, and Chirag J. Patel. 2019. “Repurposing Large Health Insurance Claims Data to Estimate Genetic and Environmental Contributions in 560 Phenotypes.” Nature Genetics 51 (2): 327–34. https://doi.org/10.1038/s41588-018-0313-7.
Laparre, Jérôme, Zied Kaabia, Mark Mooney, Tom Buckley, Mark Sherry, Bruno Le Bizec, and Gaud Dervilly-Pinel. 2017. “Impact of Storage Conditions on the Urinary Metabolomics Fingerprint.” Analytica Chimica Acta 951 (January): 99–107. https://doi.org/10.1016/j.aca.2016.11.055.
Larralde, Martin, Thomas N. Lawson, Ralf J. M. Weber, Pablo Moreno, Kenneth Haug, Philippe Rocca-Serra, Mark R. Viant, Christoph Steinbeck, and Reza M. Salek. 2017. “mzML2ISA & nmrML2ISA: Generating Enriched ISA-Tab Metadata Files from Metabolomics XML Data.” Bioinformatics 33 (16): 2598–2600. https://doi.org/10.1093/bioinformatics/btx169.
Lassen, Johan, Kirstine Lykke Nielsen, Mogens Johannsen, and Palle Villesen. 2021. “Assessment of XCMS Optimization Methods with Machine-Learning Performance.” Analytical Chemistry 93 (40): 13459–66. https://doi.org/10.1021/acs.analchem.1c02000.
Lawson, Thomas N., Ralf J. M. Weber, Martin R. Jones, Andrew J. Chetwynd, Giovanny Rodrı́guez-Blanco, Riccardo Di Guida, Mark R. Viant, and Warwick B. Dunn. 2017. “msPurity: Automated Evaluation of Precursor Ion Purity for Mass Spectrometry-Based Fragmentation in Metabolomics.” Analytical Chemistry 89 (4): 2432–39. https://doi.org/10.1021/acs.analchem.6b04358.
Lê Cao, Kim-Anh, Simon Boitard, and Philippe Besse. 2011. “Sparse PLS Discriminant Analysis: Biologically Relevant Feature Selection and Graphical Displays for Multiclass Problems.” BMC Bioinformatics 12 (June): 253. https://doi.org/10.1186/1471-2105-12-253.
Ledesma-Escobar, Carlos Augusto, Feliciano Priego-Capote, and Mónica Calderón-Santiago. 2023. “MetaboMSDIA: A Tool for Implementing Data-Independent Acquisition in Metabolomic-Based Mass Spectrometry Analysis.” Analytica Chimica Acta 1266 (July): 341308. https://doi.org/10.1016/j.aca.2023.341308.
Leek, Jeffrey T., W. Evan Johnson, Hilary S. Parker, Andrew E. Jaffe, and John D. Storey. 2012. “The Sva Package for Removing Batch Effects and Other Unwanted Variation in High-Throughput Experiments.” Bioinformatics 28 (6): 882–83. https://doi.org/10.1093/bioinformatics/bts034.
Leek, Jeffrey T., and John D. Storey. 2007. “Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis.” PLOS Genet 3 (9): e161. https://doi.org/10.1371/journal.pgen.0030161.
———. 2008. “A General Framework for Multiple Testing Dependence.” Proceedings of the National Academy of Sciences 105 (48): 18718–23. https://doi.org/10.1073/pnas.0808709105.
Levy, Allison J., Nicholas R. Oranzi, Atiye Ahmadireskety, Robin H. J. Kemperman, Michael S. Wei, and Richard A. Yost. 2019. “Recent Progress in Metabolomics Using Ion Mobility-Mass Spectrometry.” TrAC Trends in Analytical Chemistry 116 (July): 274–81. https://doi.org/10.1016/j.trac.2019.05.001.
Li, Bo, Jing Tang, Qingxia Yang, Shuang Li, Xuejiao Cui, Yinghong Li, Yuzong Chen, Weiwei Xue, Xiaofeng Li, and Feng Zhu. 2017. “NOREVA: Normalization and Evaluation of MS-based Metabolomics Data.” Nucleic Acids Research 45 (W1): W162–70. https://doi.org/10.1093/nar/gkx449.
Li, Hao, Yuping Cai, Yuan Guo, Fangfang Chen, and Zheng-Jiang Zhu. 2016. “MetDIA: Targeted Metabolite Extraction of Multiplexed MS/MS Spectra Generated by Data-Independent Acquisition.” Analytical Chemistry 88 (17): 8757–64. https://doi.org/10.1021/acs.analchem.6b02122.
Li, Liang, Ronghong Li, Jianjun Zhou, Azeret Zuniga, Avalyn E. Stanislaus, Yiman Wu, Tao Huan, et al. 2013. “MyCompoundID: Using an Evidence-Based Metabolome Library for Metabolite Identification.” Analytical Chemistry 85 (6): 3401–8. https://doi.org/10.1021/ac400099b.
Li, Lili, Weijie Ren, Hongwei Kong, Chunxia Zhao, Xinjie Zhao, Xiaohui Lin, Xin Lu, and Guowang Xu. 2017. “An Alignment Algorithm for LC-MS-based Metabolomics Dataset Assisted by MS/MS Information.” Analytica Chimica Acta 990 (October): 96–102. https://doi.org/10.1016/j.aca.2017.07.058.
Li, Shuzhao. 2020. Computational Methods and Data Analysis for Metabolomics. Springer.
Li, Shuzhao, Youngja Park, Sai Duraisingham, Frederick H. Strobel, Nooruddin Khan, Quinlyn A. Soltow, Dean P. Jones, and Bali Pulendran. 2013. “Predicting Network Activity from High Throughput Metabolomics.” PLOS Computational Biology 9 (7): e1003123. https://doi.org/10.1371/journal.pcbi.1003123.
Li, Shuzhao, Amnah Siddiqa, Maheshwor Thapa, Yuanye Chi, and Shujian Zheng. 2023. “Trackable and Scalable LC-MS Metabolomics Data Processing Using Asari.” Nature Communications 14 (1): 4113. https://doi.org/10.1038/s41467-023-39889-1.
Li, Yuanyue, and Oliver Fiehn. 2023. “Flash Entropy Search to Query All Mass Spectral Libraries in Real Time.” Nature Methods 20 (10): 1475–78. https://doi.org/10.1038/s41592-023-02012-9.
Li, Yuanyue, Tobias Kind, Jacob Folz, Arpana Vaniya, Sajjan Singh Mehta, and Oliver Fiehn. 2021. “Spectral Entropy Outperforms MS/MS Dot Product Similarity for Small-Molecule Compound Identification.” Nature Methods 18 (12): 1524–31. https://doi.org/10.1038/s41592-021-01331-z.
Li, Zhucui, Yan Lu, Yufeng Guo, Haijie Cao, Qinhong Wang, and Wenqing Shui. 2018. “Comprehensive Evaluation of Untargeted Metabolomics Data Processing Software in Feature Detection, Quantification and Discriminating Marker Selection.” Analytica Chimica Acta 1029 (October): 50–57. https://doi.org/10.1016/j.aca.2018.05.001.
Liao, Jingyu, Yuhao Zhang, Wendan Zhang, Yuanyuan Zeng, Jing Zhao, Jingfang Zhang, Tingting Yao, et al. 2023. “Different Software Processing Affects the Peak Picking and Metabolic Pathway Recognition of Metabolomics Data.” Journal of Chromatography A 1687 (January): 463700. https://doi.org/10.1016/j.chroma.2022.463700.
Libiseller, Gunnar, Michaela Dvorzak, Ulrike Kleb, Edgar Gander, Tobias Eisenberg, Frank Madeo, Steffen Neumann, et al. 2015. “IPO: A Tool for Automated Optimization of XCMS Parameters.” BMC Bioinformatics 16 (April): 118. https://doi.org/10.1186/s12859-015-0562-8.
Lieng, Brandon Y., Andrew T. Quaile, Xavier Domingo-Almenara, Hannes L. Röst, and J. Rafael Montenegro-Burke. 2023. “Computational Expansion of High-Resolution-MSn Spectral Libraries.” Analytical Chemistry, November. https://doi.org/10.1021/acs.analchem.3c03343.
Lin, Ching Yu, Huifeng Wu, Ronald S. Tjeerdema, and Mark R. Viant. 2007. “Evaluation of Metabolite Extraction Strategies from Tissue Samples Using NMR Metabolomics.” Metabolomics 3 (1): 55–67. https://doi.org/10.1007/s11306-006-0043-1.
Lisec, Jan, Friederike Hoffmann, Clemens Schmitt, and Carsten Jaeger. 2016. “Extending the Dynamic Range in Metabolomics Experiments by Automatic Correction of Peaks Exceeding the Detection Limit.” Analytical Chemistry 88 (15): 7487–92. https://doi.org/10.1021/acs.analchem.6b02515.
Lisitsyna, Anna, Franco Moritz, Youzhong Liu, Loubna Al Sadat, Hans Hauner, Melina Claussnitzer, Philippe Schmitt-Kopplin, and Sara Forcisi. 2022. “Feature Selection Pipelines with Classification for Non-targeted Metabolomics Combining the Neural Network and Genetic Algorithm.” Analytical Chemistry 94 (14): 5474–82. https://doi.org/10.1021/acs.analchem.1c03237.
Liu, Qin, Douglas Walker, Karan Uppal, Zihe Liu, Chunyu Ma, ViLinh Tran, Shuzhao Li, Dean P. Jones, and Tianwei Yu. 2020. “Addressing the Batch Effect Issue for LC/MS Metabolomics Data in Data Preprocessing.” Scientific Reports 10 (1): 13856. https://doi.org/10.1038/s41598-020-70850-0.
Liu, Xinyu, Lina Zhou, Xianzhe Shi, and Guowang Xu. 2019. “New Advances in Analytical Methods for Mass Spectrometry-Based Large-Scale Metabolomics Study.” TrAC Trends in Analytical Chemistry 121 (December): 115665. https://doi.org/10.1016/j.trac.2019.115665.
Liu, Youzhong, Yingjie Zhang, Tom Vennekens, Jennifer L. Lippens, Luc Duijsens, Danh Bui-Thi, Kris Laukens, and Thomas de Vijlder. 2023. “MeRgeION: A Multifunctional R Pipeline for Small Molecule LC-MS/MS Data Processing, Searching, and Organizing.” Analytical Chemistry 95 (22): 8433–42. https://doi.org/10.1021/acs.analchem.2c04343.
Livera, Alysha M. De, Marko Sysi-Aho, Laurent Jacob, Johann A. Gagnon-Bartsch, Sandra Castillo, Julie A. Simpson, and Terence P. Speed. 2015. “Statistical Methods for Handling Unwanted Variation in Metabolomics Data.” Analytical Chemistry 87 (7): 3606–15. https://doi.org/10.1021/ac502439y.
Loftfield, Erikka, Emily Vogtmann, Joshua N. Sampson, Steven C. Moore, Heidi Nelson, Rob Knight, Nicholas Chia, and Rashmi Sinha. 2016. “Comparison of Collection Methods for Fecal Samples for Discovery Metabolomics in Epidemiologic Studies.” Cancer Epidemiology and Prevention Biomarkers 25 (11): 1483–90. https://doi.org/10.1158/1055-9965.EPI-16-0409.
Loos, Martin, and Heinz Singer. 2017. “Nontargeted Homologue Series Extraction from Hyphenated High Resolution Mass Spectrometry Data.” Journal of Cheminformatics 9 (February). https://doi.org/10.1186/s13321-017-0197-z.
Lu, Wenyun, Bryson D. Bennett, and Joshua D. Rabinowitz. 2008. “Analytical Strategies for LC–MS-based Targeted Metabolomics.” Journal of Chromatography B, Hyphenated Techniques for Global Metabolite Profiling, 871 (2): 236–42. https://doi.org/10.1016/j.jchromb.2008.04.031.
Lu, Wenyun, Xiaoyang Su, Matthias S. Klein, Ian A. Lewis, Oliver Fiehn, and Joshua D. Rabinowitz. 2017. “Metabolite Measurement: Pitfalls to Avoid and Practices to Follow.” Annual Review of Biochemistry 86 (1): 277–304. https://doi.org/10.1146/annurev-biochem-061516-044952.
Lu, Xin, and Guowang Xu. 2008. “LC-MS Metabonomics Methodology in Biomarker Discovery.” In Biomarker Methods in Drug Discovery and Development, edited by Feng Wang, 291–315. Methods in Pharmacology and Toxicology™. Humana Press. https://doi.org/10.1007/978-1-59745-463-6_14.
Ludwig, Marcus, Louis-Félix Nothias, Kai Dührkop, Irina Koester, Markus Fleischauer, Martin A. Hoffmann, Daniel Petras, et al. 2020. “Database-Independent Molecular Formula Annotation Using Gibbs Sampling Through ZODIAC.” Nature Machine Intelligence 2 (10): 629–41. https://doi.org/10.1038/s42256-020-00234-6.
Luo, Xian, and Liang Li. 2017. “Metabolomics of Small Numbers of Cells: Metabolomic Profiling of 100, 1000, and 10000 Human Breast Cancer Cells.” Analytical Chemistry 89 (21): 11664–71. https://doi.org/10.1021/acs.analchem.7b03100.
Lv, Wangjie, Zhongda Zeng, Yuqing Zhang, Qingqing Wang, Lichao Wang, Zhaoxuan Zhang, Xianzhe Shi, Xinjie Zhao, and Guowang Xu. 2022. “Comprehensive Metabolite Quantitative Assay Based on Alternate Metabolomics and Lipidomics Analyses.” Analytica Chimica Acta 1215 (July): 339979. https://doi.org/10.1016/j.aca.2022.339979.
Ma, Yan, Tobias Kind, Dawei Yang, Carlos Leon, and Oliver Fiehn. 2014. “MS2Analyzer: A Software for Small Molecule Substructure Annotations from Accurate Tandem Mass Spectra.” Analytical Chemistry 86 (21): 10724–31. https://doi.org/10.1021/ac502818e.
Madsen, Rasmus, Torbjörn Lundstedt, and Johan Trygg. 2010. “Chemometrics in Metabolomics—A Review in Human Disease Diagnosis.” Analytica Chimica Acta 659 (1): 23–33. https://doi.org/10.1016/j.aca.2009.11.042.
Mahieu, Nathaniel G., and Gary J. Patti. 2017. “Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer Than 1000 Unique Metabolites.” Analytical Chemistry 89 (19): 10397–406. https://doi.org/10.1021/acs.analchem.7b02380.
Mahieu, Nathaniel G., Jonathan L. Spalding, Susan J. Gelman, and Gary J. Patti. 2016. “Defining and Detecting Complex Peak Relationships in Mass Spectral Data: The Mz.unity Algorithm.” Analytical Chemistry 88 (18): 9037–46. https://doi.org/10.1021/acs.analchem.6b01702.
Mahieu, Nathaniel G., Jonathan L. Spalding, and Gary J. Patti. 2016. “Warpgroup: Increased Precision of Metabolomic Data Processing by Consensus Integration Bound Analysis.” Bioinformatics 32 (2): 268–75. https://doi.org/10.1093/bioinformatics/btv564.
Mahmud, Iqbal, Sandi Sternberg, Michael Williams, and Timothy J. Garrett. 2017. “Comparison of Global Metabolite Extraction Strategies for Soybeans Using UHPLC-HRMS.” Analytical and Bioanalytical Chemistry 409 (26): 6173–80. https://doi.org/10.1007/s00216-017-0557-6.
Maitre, Léa, Mariona Bustamante, Carles Hernández-Ferrer, Denise Thiel, Chung-Ho E. Lau, Alexandros P. Siskos, Marta Vives-Usano, et al. 2022. “Multi-Omics Signatures of the Human Early Life Exposome.” Nature Communications 13 (1): 7024. https://doi.org/10.1038/s41467-022-34422-2.
Mangul, Serghei, Thiago Mosqueiro, Richard J. Abdill, Dat Duong, Keith Mitchell, Varuni Sarwal, Brian Hill, et al. 2019. “Challenges and Recommendations to Improve the Installability and Archival Stability of Omics Computational Tools.” PLOS Biology 17 (6): e3000333. https://doi.org/10.1371/journal.pbio.3000333.
Mannhold, Raimund, Gennadiy I. Poda, Claude Ostermann, and Igor V. Tetko. 2009. “Calculation of Molecular Lipophilicity: State-of-the-Art and Comparison of LogP Methods on More Than 96,000 Compounds.” Journal of Pharmaceutical Sciences 98 (3): 861–93. https://doi.org/10.1002/jps.21494.
Mansouri, Kamel, Chris M. Grulke, Richard S. Judson, and Antony J. Williams. 2018. “OPERA Models for Predicting Physicochemical Properties and Environmental Fate Endpoints.” Journal of Cheminformatics 10 (1): 10. https://doi.org/10.1186/s13321-018-0263-1.
Mardal, Marie, Petur W. Dalsgaard, Brian S. Rasmussen, Kristian Linnet, and Christian B. Mollerup. 2023. “Scalable Analysis of Untargeted LC-HRMS Data by Means of SQL Database Archiving.” Analytical Chemistry, February. https://doi.org/10.1021/acs.analchem.2c03769.
Martens, Jonathan, Giel Berden, Rianne E. van Outersterp, Leo A. J. Kluijtmans, Udo F. Engelke, Clara D. M. van Karnebeek, Ron A. Wevers, and Jos Oomens. 2017. “Molecular Identification in Metabolomics Using Infrared Ion Spectroscopy.” Scientific Reports 7 (June). https://doi.org/10.1038/s41598-017-03387-4.
Matich, Eryn K., Nita G. Chavez Soria, Diana S. Aga, and G. Ekin Atilla-Gokcumen. 2019. “Applications of Metabolomics in Assessing Ecological Effects of Emerging Contaminants and Pollutants on Plants.” Journal of Hazardous Materials 373 (July): 527–35. https://doi.org/10.1016/j.jhazmat.2019.02.084.
Matsuo, Teruko, Hiroshi Tsugawa, Hiromi Miyagawa, and Eiichiro Fukusaki. 2017. “Integrated Strategy for Unknown EI–MS Identification Using Quality Control Calibration Curve, Multivariate Analysis, EI–MS Spectral Database, and Retention Index Prediction.” Analytical Chemistry 89 (12): 6766–73. https://doi.org/10.1021/acs.analchem.7b01010.
McLean, Craig, and Elizabeth B. Kujawinski. 2020. “AutoTuner: High Fidelity and Robust Parameter Selection for Metabolomics Data Processing.” Analytical Chemistry 92 (8): 5724–32. https://doi.org/10.1021/acs.analchem.9b04804.
Melamud, Eugene, Livia Vastag, and Joshua D. Rabinowitz. 2010. “Metabolomic Analysis and Visualization Engine for LC-MS Data.” Analytical Chemistry 82 (23): 9818–26. https://doi.org/10.1021/ac1021166.
Menikarachchi, Lochana C., Shannon Cawley, Dennis W. Hill, L. Mark Hall, Lowell Hall, Steven Lai, Janine Wilder, and David F. Grant. 2012. “MolFind: A Software Package Enabling HPLC/MS-Based Identification of Unknown Chemical Structures.” Analytical Chemistry 84 (21): 9388–94. https://doi.org/10.1021/ac302048x.
Miggiels, Paul, Bert Wouters, Gerard J. P. van Westen, Anne-Charlotte Dubbelman, and Thomas Hankemeier. 2019. “Novel Technologies for Metabolomics: More for Less.” TrAC Trends in Analytical Chemistry 120 (November): 115323. https://doi.org/10.1016/j.trac.2018.11.021.
Misra, Biswapriya B. 2018. “New Tools and Resources in Metabolomics: 2016–2017.” ELECTROPHORESIS 39 (7): 909–23. https://doi.org/10.1002/elps.201700441.
Misra, Biswapriya B., Johannes F. Fahrmann, and Dmitry Grapov. 2017. “Review of Emerging Metabolomic Tools and Resources: 2015–2016.” ELECTROPHORESIS 38 (18): 2257–74. https://doi.org/10.1002/elps.201700110.
Misra, Biswapriya B., and Justin J. J. van der Hooft. 2016. “Updates in Metabolomics Tools and Resources: 2014–2015.” ELECTROPHORESIS 37 (1): 86–110. https://doi.org/10.1002/elps.201500417.
Miyagawa, Hiromi, and Takeshi Bamba. 2019. “Comparison of Sequential Derivatization with Concurrent Methods for GC/MS-based Metabolomics.” Journal of Bioscience and Bioengineering 127 (2): 160–68. https://doi.org/10.1016/j.jbiosc.2018.07.015.
Montenegro-Burke, J. Rafael, Aries E. Aisporna, H. Paul Benton, Duane Rinehart, Mingliang Fang, Tao Huan, Benedikt Warth, et al. 2017. “Data Streaming for Metabolomics: Accelerating Data Processing and Analysis from Days to Minutes.” Analytical Chemistry 89 (2): 1254–59. https://doi.org/10.1021/acs.analchem.6b03890.
Müller, Manfred J., and Anja Bosy-Westphal. 2020. “From a ‘Metabolomics Fashion’ to a Sound Application of Metabolomics in Research on Human Nutrition.” European Journal of Clinical Nutrition 74 (12): 1619–29. https://doi.org/10.1038/s41430-020-00781-6.
Myers, Owen D., Susan J. Sumner, Shuzhao Li, Stephen Barnes, and Xiuxia Du. 2017. “Detailed Investigation and Comparison of the XCMS and MZmine 2 Chromatogram Construction and Chromatographic Peak Detection Methods for Preprocessing Mass Spectrometry Metabolomics Data.” Analytical Chemistry 89 (17): 8689–95. https://doi.org/10.1021/acs.analchem.7b01069.
Najdekr, Lukáš, David Friedecký, Ralf Tautenhahn, Tomáš Pluskal, Junhua Wang, Yingying Huang, and Tomáš Adam. 2016. “Influence of Mass Resolving Power in Orbital Ion-Trap Mass Spectrometry-Based Metabolomics.” Analytical Chemistry 88 (23): 11429–35. https://doi.org/10.1021/acs.analchem.6b02319.
Nash, William J., and Warwick B. Dunn. 2019. “From Mass to Metabolite in Human Untargeted Metabolomics: Recent Advances in Annotation of Metabolites Applying Liquid Chromatography-Mass Spectrometry Data.” TrAC Trends in Analytical Chemistry 120 (November): 115324. https://doi.org/10.1016/j.trac.2018.11.022.
Ni, Yan, Mingming Su, Yunping Qiu, Wei Jia, and Xiuxia Du. 2016. “ADAP-GC 3.0: Improved Peak Detection and Deconvolution of Co-eluting Metabolites from GC/TOF-MS Data for Metabolomics Studies.” Analytical Chemistry 88 (17): 8802–11. https://doi.org/10.1021/acs.analchem.6b02222.
Ni, Zhixu, Michele Wölk, Geoff Jukes, Karla Mendivelso Espinosa, Robert Ahrends, Lucila Aimo, Jorge Alvarez-Jarreta, et al. 2022. “Guiding the Choice of Informatics Software and Tools for Lipidomics Research Applications.” Nature Methods, December, 1–12. https://doi.org/10.1038/s41592-022-01710-0.
Nikolskiy, Igor, Nathaniel G. Mahieu, Ying-Jr Chen, Ralf Tautenhahn, and Gary J. Patti. 2013. “An Untargeted Metabolomic Workflow to Improve Structural Characterization of Metabolites.” Analytical Chemistry 85 (16): 7713–19. https://doi.org/10.1021/ac400751j.
Nothias, Louis-Félix, Daniel Petras, Robin Schmid, Kai Dührkop, Johannes Rainer, Abinesh Sarvepalli, Ivan Protsyuk, et al. 2020. “Feature-Based Molecular Networking in the GNPS Analysis Environment.” Nature Methods 17 (9): 905–8. https://doi.org/10.1038/s41592-020-0933-6.
Nyamundanda, Gift, Isobel Claire Gormley, Yue Fan, William M. Gallagher, and Lorraine Brennan. 2013. “MetSizeR: Selecting the Optimal Sample Size for Metabolomic Studies Using an Analysis Based Approach.” BMC Bioinformatics 14: 338. https://doi.org/10.1186/1471-2105-14-338.
O’Boyle, Noel M., Michael Banck, Craig A. James, Chris Morley, Tim Vandermeersch, and Geoffrey R. Hutchison. 2011. “Open Babel: An Open Chemical Toolbox.” Journal of Cheminformatics 3 (1): 33. https://doi.org/10.1186/1758-2946-3-33.
Oberg, Ann L., and Olga Vitek. 2009. “Statistical Design of Quantitative Mass Spectrometry-Based Proteomic Experiments.” Journal of Proteome Research 8 (5): 2144–56. https://doi.org/10.1021/pr8010099.
Ortmayr, Karin, Verena Charwat, Cornelia Kasper, Stephan Hann, and Gunda Koellensperger. 2016. “Uncertainty Budgeting in Fold Change Determination and Implications for Non-Targeted Metabolomics Studies in Model Systems” 142 (1): 80–90. https://doi.org/10.1039/C6AN01342B.
Osipenko, Sergey, Alexander Zherebker, Lidiia Rumiantseva, Oxana Kovaleva, Evgeny N. Nikolaev, and Yury Kostyukevich. 2022. “Oxygen Isotope Exchange Reaction for Untargeted LC–MS Analysis.” Journal of the American Society for Mass Spectrometry 33 (2): 390–98. https://doi.org/10.1021/jasms.1c00383.
Palmer, Andrew, Prasad Phapale, Ilya Chernyavsky, Regis Lavigne, Dominik Fay, Artem Tarasov, Vitaly Kovalev, et al. 2017. “FDR-controlled Metabolite Annotation for High-Resolution Imaging Mass Spectrometry.” Nature Methods 14 (1): 57–60. https://doi.org/10.1038/nmeth.4072.
Pang, Zhiqiang, Jasmine Chong, Shuzhao Li, and Jianguo Xia. 2020. “MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics.” Metabolites 10 (5): 186. https://doi.org/10.3390/metabo10050186.
Passos Mansoldo, Felipe Raposo, Rafael Garrett, Veronica da Silva Cardoso, Marina Amaral Alves, and Alane Beatriz Vermelho. 2022. “Metabology: Analysis of Metabolomics Data Using Community Ecology Tools.” Analytica Chimica Acta 1232 (November): 340469. https://doi.org/10.1016/j.aca.2022.340469.
Patiny, Luc, and Alain Borel. 2013. “ChemCalc: A Building Block for Tomorrow’s Chemical Infrastructure.” Journal of Chemical Information and Modeling 53 (5): 1223–28. https://doi.org/10.1021/ci300563h.
Petras, Daniel, Vanessa V. Phelan, Deepa Acharya, Andrew E. Allen, Allegra T. Aron, Nuno Bandeira, Benjamin P. Bowen, et al. 2021. “GNPS Dashboard: Collaborative Exploration of Mass Spectrometry Data in the Web Browser.” Nature Methods, December, 1–3. https://doi.org/10.1038/s41592-021-01339-5.
Pezzatti, Julian, Julien Boccard, Santiago Codesido, Yoric Gagnebin, Abhinav Joshi, Didier Picard, Víctor González-Ruiz, and Serge Rudaz. 2020. “Implementation of Liquid Chromatography–High Resolution Mass Spectrometry Methods for Untargeted Metabolomic Analyses of Biological Samples: A Tutorial.” Analytica Chimica Acta 1105 (April): 28–44. https://doi.org/10.1016/j.aca.2019.12.062.
Pfeuffer, Julianus, Chris Bielow, Samuel Wein, Kyowon Jeong, Eugen Netz, Axel Walter, Oliver Alka, et al. 2024. “OpenMS 3 Enables Reproducible Analysis of Large-Scale Mass Spectrometry Data.” Nature Methods 21 (3): 365–67. https://doi.org/10.1038/s41592-024-02197-7.
Pfeuffer, Julianus, Timo Sachsenberg, Oliver Alka, Mathias Walzer, Alexander Fillbrunn, Lars Nilse, Oliver Schilling, Knut Reinert, and Oliver Kohlbacher. 2017. “OpenMS – A Platform for Reproducible Analysis of Mass Spectrometry Data.” Journal of Biotechnology, Bioinformatics Solutions for Big Data Analysis in Life Sciences presented by the German Network for Bioinformatics Infrastructure, 261 (November): 142–48. https://doi.org/10.1016/j.jbiotec.2017.05.016.
Phapale, Prasad, Vineeta Rai, Ashok Kumar Mohanty, and Sanjeeva Srivastava. 2020. “Untargeted Metabolomics Workshop Report: Quality Control Considerations from Sample Preparation to Data Analysis.” Journal of the American Society for Mass Spectrometry 31 (9): 2006–10. https://doi.org/10.1021/jasms.0c00224.
Place, Benjamin J., Elin M. Ulrich, Jonathan K. Challis, Alex Chao, Bowen Du, Kristin Favela, Yong-Lai Feng, et al. 2021. “An Introduction to the Benchmarking and Publications for Non-Targeted Analysis Working Group.” Analytical Chemistry 93 (49): 16289–96. https://doi.org/10.1021/acs.analchem.1c02660.
Pluskal, Tomáš, Sandra Castillo, Alejandro Villar-Briones, and Matej Orešič. 2010. “MZmine 2: Modular Framework for Processing, Visualizing, and Analyzing Mass Spectrometry-Based Molecular Profile Data.” BMC Bioinformatics 11: 395. https://doi.org/10.1186/1471-2105-11-395.
Pluskal, Tomáš, Ansgar Korf, Aleksandr Smirnov, Robin Schmid, Timothy R. Fallon, Xiuxia Du, and Jing-Ke Weng. 2020. “CHAPTER 7:Metabolomics Data Analysis Using MZmine.” In Processing Metabolomics and Proteomics Data with Open Software, 232–54. https://doi.org/10.1039/9781788019880-00232.
Plyushchenko, Ivan V., Elizaveta S. Fedorova, Natalia V. Potoldykova, Konstantin A. Polyakovskiy, Alexander I. Glukhov, and Igor A. Rodin. 2022. “Omics Untargeted Key Script: R-Based Software Toolbox for Untargeted Metabolomics with Bladder Cancer Biomarkers Discovery Case Study.” Journal of Proteome Research 21 (3): 833–47. https://doi.org/10.1021/acs.jproteome.1c00392.
Polderman, Tinca J. C., Beben Benyamin, Christiaan A. de Leeuw, Patrick F. Sullivan, Arjen van Bochoven, Peter M. Visscher, and Danielle Posthuma. 2015. “Meta-Analysis of the Heritability of Human Traits Based on Fifty Years of Twin Studies.” Nature Genetics 47 (7): 702–9. https://doi.org/10.1038/ng.3285.
Qiu, Feng, Dennis D. Fine, Daniel J. Wherritt, Zhentian Lei, and Lloyd W. Sumner. 2016. “PlantMAT: A Metabolomics Tool for Predicting the Specialized Metabolic Potential of a System and for Large-Scale Metabolite Identifications.” Analytical Chemistry 88 (23): 11373–83. https://doi.org/10.1021/acs.analchem.6b00906.
Qiu, Feng, Zhentian Lei, and Lloyd W. Sumner. 2018. “MetExpert: An Expert System to Enhance Gas Chromatography-Mass Spectrometry-Based Metabolite Identifications.” Analytica Chimica Acta, Analytical Metabolomics, 1037 (December): 316–26. https://doi.org/10.1016/j.aca.2018.03.052.
Reuschenbach, Max, Felix Drees, Torsten C. Schmidt, and Gerrit Renner. 2023. “qBinning: Data Quality-Based Algorithm for Automized Ion Chromatogram Extraction from High-Resolution Mass Spectrometry.” Analytical Chemistry, September. https://doi.org/10.1021/acs.analchem.3c01079.
Rey-Stolle, Fernanda, Danuta Dudzik, Carolina Gonzalez-Riano, Miguel Fernández-García, Vanesa Alonso-Herranz, David Rojo, Coral Barbas, and Antonia García. 2022. “Low and High Resolution Gas Chromatography-Mass Spectrometry for Untargeted Metabolomics: A Tutorial.” Analytica Chimica Acta 1210 (June): 339043. https://doi.org/10.1016/j.aca.2021.339043.
Riquelme, Gabriel, Nicolás Zabalegui, Pablo Marchi, Christina M. Jones, and María Eugenia Monge. 2020. “A Python-Based Pipeline for Preprocessing LC–MS Data for Untargeted Metabolomics Workflows.” Metabolites 10 (10): 416. https://doi.org/10.3390/metabo10100416.
Röst, Hannes L., Timo Sachsenberg, Stephan Aiche, Chris Bielow, Hendrik Weisser, Fabian Aicheler, Sandro Andreotti, et al. 2016. “OpenMS: A Flexible Open-Source Software Platform for Mass Spectrometry Data Analysis.” Nature Methods 13 (9): 741–48. https://doi.org/10.1038/nmeth.3959.
Röst, Hannes L., Uwe Schmitt, Ruedi Aebersold, and Lars Malmström. 2014. “pyOpenMS: A Python-based Interface to the OpenMS Mass-Spectrometry Algorithm Library.” PROTEOMICS 14 (1): 74–77. https://doi.org/10.1002/pmic.201300246.
Roszkowska, Anna, Miao Yu, Vincent Bessonneau, Leslie Bragg, Mark Servos, and Janusz Pawliszyn. 2018. “Tissue Storage Affects Lipidome Profiling in Comparison to in Vivo Microsampling Approach.” Scientific Reports 8 (1): 6980. https://doi.org/10.1038/s41598-018-25428-2.
Rurik, Marc, Oliver Alka, Fabian Aicheler, and Oliver Kohlbacher. 2020. “Metabolomics Data Processing Using OpenMS.” In Computational Methods and Data Analysis for Metabolomics, edited by Shuzhao Li, 49–60. Methods in Molecular Biology. New York, NY: Springer US. https://doi.org/10.1007/978-1-0716-0239-3_4.
Rusconi, Filippo. 2019. “mineXpert: Biological Mass Spectrometry Data Visualization and Mining with Full JavaScript Ability.” Journal of Proteome Research 18 (5): 2254–59. https://doi.org/10.1021/acs.jproteome.9b00099.
Ruttkies, Christoph, Emma L. Schymanski, Sebastian Wolf, Juliane Hollender, and Steffen Neumann. 2016. “MetFrag Relaunched: Incorporating Strategies Beyond in Silico Fragmentation.” Journal of Cheminformatics 8 (January): 3. https://doi.org/10.1186/s13321-016-0115-9.
Saccenti, Edoardo, and Marieke E. Timmerman. 2016. “Approaches to Sample Size Determination for Multivariate Data: Applications to PCA and PLS-DA of Omics Data.” Journal of Proteome Research 15 (8): 2379–93. https://doi.org/10.1021/acs.jproteome.5b01029.
Samanipour, Saer, Malcolm J. Reid, Kine Bæk, and Kevin V. Thomas. 2018. “Combining a Deconvolution and a Universal Library Search Algorithm for the Nontarget Analysis of Data-Independent Acquisition Mode Liquid Chromatography-High-Resolution Mass Spectrometry Results.” Environmental Science & Technology 52 (8): 4694–4701. https://doi.org/10.1021/acs.est.8b00259.
Sarpe, Vladimir, and David C Schriemer. 2017. “Supporting Metabolomics with Adaptable Software: Design Architectures for the End-User.” Current Opinion in Biotechnology, Analytical biotechnology, 43 (February): 110–17. https://doi.org/10.1016/j.copbio.2016.11.001.
Scheltema, Richard A., Andris Jankevics, Ritsert C. Jansen, Morris A. Swertz, and Rainer Breitling. 2011. “PeakML/mzMatch: A File Format, Java Library, R Library, and Tool-Chain for Mass Spectrometry Data Analysis.” Analytical Chemistry 83 (7): 2786–93. https://doi.org/10.1021/ac2000994.
Scheubert, Kerstin, Franziska Hufsky, Daniel Petras, Mingxun Wang, Louis-Félix Nothias, Kai Dührkop, Nuno Bandeira, Pieter C. Dorrestein, and Sebastian Böcker. 2017. “Significance Estimation for Large Scale Metabolomics Annotations by Spectral Matching.” Nature Communications 8 (1): 1494. https://doi.org/10.1038/s41467-017-01318-5.
Schrimpe-Rutledge, Alexandra C., Simona G. Codreanu, Stacy D. Sherrod, and John A. McLean. 2016. “Untargeted Metabolomics Strategies—Challenges and Emerging Directions.” Journal of The American Society for Mass Spectrometry 27 (12): 1897–1905. https://doi.org/10.1007/s13361-016-1469-y.
Schymanski, Emma L., and Antony J. Williams. 2017. “Open Science for Identifying ‘Known Unknown’ Chemicals.” Environmental Science & Technology 51 (10): 5357–59. https://doi.org/10.1021/acs.est.7b01908.
Senan, Oriol, Antoni Aguilar-Mogas, Miriam Navarro, Jordi Capellades, Luke Noon, Deborah Burks, Oscar Yanes, Roger Guimerà, and Marta Sales-Pardo. 2019. “CliqueMS: A Computational Tool for Annotating in-Source Metabolite Ions from LC-MS Untargeted Metabolomics Data Based on a Coelution Similarity Network.” Bioinformatics 35 (20): 4089–97. https://doi.org/10.1093/bioinformatics/btz207.
Shaffer, Justin P., Louis-Félix Nothias, Luke R. Thompson, Jon G. Sanders, Rodolfo A. Salido, Sneha P. Couvillion, Asker D. Brejnrod, et al. 2022. “Standardized Multi-Omics of Earth’s Microbiomes Reveals Microbial and Metabolite Diversity.” Nature Microbiology 7 (12): 2128–50. https://doi.org/10.1038/s41564-022-01266-x.
Shen, Xiaotao, Ruohong Wang, Xin Xiong, Yandong Yin, Yuping Cai, Zaijun Ma, Nan Liu, and Zheng-Jiang Zhu. 2019. “Metabolic Reaction Network-Based Recursive Metabolite Annotation for Untargeted Metabolomics.” Nature Communications 10 (1): 1–14. https://doi.org/10.1038/s41467-019-09550-x.
Shen, Xiaotao, Hong Yan, Chuchu Wang, Peng Gao, Caroline H. Johnson, and Michael P. Snyder. 2022. “TidyMass an Object-Oriented Reproducible Analysis Framework for LC–MS Data.” Nature Communications 13 (1): 4365. https://doi.org/10.1038/s41467-022-32155-w.
Shi, Jiachen, Jialiang Zhao, Yu Zhang, Yanan Wang, Chin Ping Tan, Yong-Jiang Xu, and Yuanfa Liu. 2023. “Windows Scanning Multiomics: Integrated Metabolomics and Proteomics.” Analytical Chemistry, December. https://doi.org/10.1021/acs.analchem.3c03785.
Silva, Ricardo R. da, Mingxun Wang, Louis-Félix Nothias, Justin J. J. van der Hooft, Andrés Mauricio Caraballo-Rodríguez, Evan Fox, Marcy J. Balunas, Jonathan L. Klassen, Norberto Peporine Lopes, and Pieter C. Dorrestein. 2018. “Propagating Annotations of Molecular Networks Using in Silico Fragmentation.” PLOS Computational Biology 14 (4): e1006089. https://doi.org/10.1371/journal.pcbi.1006089.
Silva, Ricardo R., Fabien Jourdan, Diego M. Salvanha, Fabien Letisse, Emilien L. Jamin, Simone Guidetti-Gonzalez, Carlos A. Labate, and Ricardo Z. N. Vêncio. 2014. “ProbMetab: An R Package for Bayesian Probabilistic Annotation of LC–MS-based Metabolomics.” Bioinformatics 30 (9): 1336–37. https://doi.org/10.1093/bioinformatics/btu019.
Sindelar, Miriam, and Gary J. Patti. 2020. “Chemical Discovery in the Era of Metabolomics.” Journal of the American Chemical Society, April. https://doi.org/10.1021/jacs.9b13198.
Siskos, Alexandros P., Pooja Jain, Werner Römisch-Margl, Mark Bennett, David Achaintre, Yasmin Asad, Luke Marney, et al. 2017. “Interlaboratory Reproducibility of a Targeted Metabolomics Platform for Analysis of Human Serum and Plasma.” Analytical Chemistry 89 (1): 656–65. https://doi.org/10.1021/acs.analchem.6b02930.
Sitnikov, Dmitri G., Cian S. Monnin, and Dajana Vuckovic. 2016. “Systematic Assessment of Seven Solvent and Solid-Phase Extraction Methods for Metabolomics Analysis of Human Plasma by LC-MS.” Scientific Reports 6 (December). https://doi.org/10.1038/srep38885.
Smirnov, Kirill S., Sara Forcisi, Franco Moritz, Marianna Lucio, and Philippe Schmitt-Kopplin. 2019. “Mass Difference Maps and Their Application for the Recalibration of Mass Spectrometric Data in Nontargeted Metabolomics.” Analytical Chemistry 91 (5): 3350–58. https://doi.org/10.1021/acs.analchem.8b04555.
Smirnov, Kirill S., Tanja V. Maier, Alesia Walker, Silke S. Heinzmann, Sara Forcisi, Inés Martinez, Jens Walter, and Philippe Schmitt-Kopplin. 2016. “Challenges of Metabolomics in Human Gut Microbiota Research.” International Journal of Medical Microbiology, Intestinal microbiota - a microbial ecosystem at the edge between immune homeostasis and inflammation, 306 (5): 266–79. https://doi.org/10.1016/j.ijmm.2016.03.006.
Smith, Colin A., Elizabeth J. Want, Grace O’Maille, Ruben Abagyan, and Gary Siuzdak. 2006. “XCMS: Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification.” Analytical Chemistry 78 (3): 779–87. https://doi.org/10.1021/ac051437y.
Spalding, Jonathan L., Kevin Cho, Nathaniel G. Mahieu, Igor Nikolskiy, Elizabeth M. Llufrio, Stephen L. Johnson, and Gary J. Patti. 2016. “Bar Coding MS2 Spectra for Metabolite Identification.” Analytical Chemistry 88 (5): 2538–42. https://doi.org/10.1021/acs.analchem.5b04925.
Spicer, Rachel, Reza M. Salek, Pablo Moreno, Daniel Cañueto, and Christoph Steinbeck. 2017. “Navigating Freely-Available Software Tools for Metabolomics Analysis.” Metabolomics 13 (9). https://doi.org/10.1007/s11306-017-1242-7.
Spratlin, Jennifer L., Natalie J. Serkova, and S. Gail Eckhardt. 2009. “Clinical Applications of Metabolomics in Oncology: A Review.” Clinical Cancer Research 15 (2): 431–40. https://doi.org/10.1158/1078-0432.CCR-08-1059.
Stancliffe, Ethan, Michaela Schwaiger-Haber, Miriam Sindelar, Matthew J. Murphy, Mette Soerensen, and Gary J. Patti. 2022. “An Untargeted Metabolomics Workflow That Scales to Thousands of Samples for Population-Based Studies.” Analytical Chemistry, December. https://doi.org/10.1021/acs.analchem.2c01270.
Stincone, Paolo, Abzer K. Pakkir Shah, Robin Schmid, Lana G. Graves, Stilianos P. Lambidis, Ralph R. Torres, Shu-Ning Xia, et al. 2023. “Evaluation of Data-Dependent MS/MS Acquisition Parameters for Non-Targeted Metabolomics and Molecular Networking of Environmental Samples: Focus on the Q Exactive Platform.” Evaluation of Data-Dependent MS/MS Acquisition Parameters for Non-Targeted Metabolomics and Molecular Networking of Environmental Samples: Focus on the Q Exactive Platform, August. https://doi.org/10.1021/acs.analchem.3c01202.
Styczynski, Mark P., Joel F. Moxley, Lily V. Tong, Jason L. Walther, Kyle L. Jensen, and Gregory N. Stephanopoulos. 2007. “Systematic Identification of Conserved Metabolites in GC/MS Data for Metabolomics and Biomarker Discovery.” Analytical Chemistry 79 (3): 966–73. https://doi.org/10.1021/ac0614846.
Sumner, Lloyd W., Alexander Amberg, Dave Barrett, Michael H. Beale, Richard Beger, Clare A. Daykin, Teresa W.-M. Fan, et al. 2007. “Proposed Minimum Reporting Standards for Chemical Analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI).” Metabolomics : Official Journal of the Metabolomic Society 3 (3): 211–21. https://doi.org/10.1007/s11306-007-0082-2.
Sumner, Lloyd W, Pedro Mendes, and Richard A Dixon. 2003. “Plant Metabolomics: Large-Scale Phytochemistry in the Functional Genomics Era.” Phytochemistry, Plant Metabolomics, 62 (6): 817–36. https://doi.org/10.1016/S0031-9422(02)00708-2.
Sysi-Aho, Marko, Mikko Katajamaa, Laxman Yetukuri, and Matej Orešič. 2007. “Normalization Method for Metabolomics Data Using Optimal Selection of Multiple Internal Standards.” BMC Bioinformatics 8 (March): 93. https://doi.org/10.1186/1471-2105-8-93.
Tang, Yanan, Caley B. Craven, Nicholas J. P. Wawryk, Junlang Qiu, Feng Li, and Xing-Fang Li. 2020. “Advances in Mass Spectrometry-Based Omics Analysis of Trace Organics in Water.” TrAC Trends in Analytical Chemistry 128 (July): 115918. https://doi.org/10.1016/j.trac.2020.115918.
Tarakhovskaya, Elena, Andrea Marcillo, Caroline Davis, Sanja Milkovska-Stamenova, Antje Hutschenreuther, and Claudia Birkemeyer. 2023. “Matrix Effects in GC-MS Profiling of Common Metabolites After Trimethylsilyl Derivatization.” Molecules (Basel, Switzerland) 28 (6): 2653. https://doi.org/10.3390/molecules28062653.
Tautenhahn, Ralf, Christoph Böttcher, and Steffen Neumann. 2008. “Highly Sensitive Feature Detection for High Resolution LC/MS.” BMC Bioinformatics 9: 504. https://doi.org/10.1186/1471-2105-9-504.
Tautenhahn, Ralf, Kevin Cho, Winnie Uritboonthai, Zhengjiang Zhu, Gary J. Patti, and Gary Siuzdak. 2012. “An Accelerated Workflow for Untargeted Metabolomics Using the METLIN Database.” Nature Biotechnology 30 (9): 826–28. https://doi.org/10.1038/nbt.2348.
Theodoridis, Georgios A., Helen G. Gika, Elizabeth J. Want, and Ian D. Wilson. 2012. “Liquid Chromatography–Mass Spectrometry Based Global Metabolite Profiling: A Review.” Analytica Chimica Acta 711 (January): 7–16. https://doi.org/10.1016/j.aca.2011.09.042.
Thonusin, Chanisa, Heidi B. IglayReger, Tanu Soni, Amy E. Rothberg, Charles F. Burant, and Charles R. Evans. 2017. “Evaluation of Intensity Drift Correction Strategies Using MetaboDrift, a Normalization Tool for Multi-Batch Metabolomics Data.” Journal of Chromatography A, Pushing the Boundaries of Chromatography and Electrophoresis, 1523 (Supplement C): 265–74. https://doi.org/10.1016/j.chroma.2017.09.023.
Tian, Leqi, Zhenjiang Li, Guoxuan Ma, Xiaoyue Zhang, Ziyin Tang, Siheng Wang, Jian Kang, Donghai Liang, and Tianwei Yu. 2022. “Metapone: A Bioconductor Package for Joint Pathway Testing for Untargeted Metabolomics Data.” Bioinformatics 38 (14): 3662–64. https://doi.org/10.1093/bioinformatics/btac364.
Tian, Tze-Feng, San-Yuan Wang, Tien-Chueh Kuo, Cheng-En Tan, Guan-Yuan Chen, Ching-Hua Kuo, Chi-Hsin Sally Chen, Chang-Chuan Chan, Olivia A. Lin, and Y. Jane Tseng. 2016. “Web Server for Peak Detection, Baseline Correction, and Alignment in Two-Dimensional Gas Chromatography Mass Spectrometry-Based Metabolomics Data.” Analytical Chemistry 88 (21): 10395–403. https://doi.org/10.1021/acs.analchem.6b00755.
Tian, Zhitao, Xin Hu, Yingying Xu, Mengmeng Liu, Hongbo Liu, Dongqin Li, Lisong Hu, Guozhu Wei, and Wei Chen. 2023. “PMhub 1.0: A Comprehensive Plant Metabolome Database.” Nucleic Acids Research, October, gkad811. https://doi.org/10.1093/nar/gkad811.
Torigoe, Taihei, Masatomo Takahashi, Omidreza Heravizadeh, Kazuki Ikeda, Kohta Nakatani, Takeshi Bamba, and Yoshihiro Izumi. 2024. “Predicting Retention Time in Unified-Hydrophilic-Interaction/Anion-Exchange Liquid Chromatography High-Resolution Tandem Mass Spectrometry (Unified-HILIC/AEX/HRMS/MS) for Comprehensive Structural Annotation of Polar Metabolome.” Analytical Chemistry 96 (3): 1275–83. https://doi.org/10.1021/acs.analchem.3c04618.
Treutler, Hendrik, and Steffen Neumann. 2016. “Prediction, Detection, and Validation of Isotope Clusters in Mass Spectrometry Data.” Metabolites 6 (4): 37. https://doi.org/10.3390/metabo6040037.
Treutler, Hendrik, Hiroshi Tsugawa, Andrea Porzel, Karin Gorzolka, Alain Tissier, Steffen Neumann, and Gerd Ulrich Balcke. 2016. “Discovering Regulated Metabolite Families in Untargeted Metabolomics Studies.” Analytical Chemistry 88 (16): 8082–90. https://doi.org/10.1021/acs.analchem.6b01569.
Tsou, Chih-Chiang, Dmitry Avtonomov, Brett Larsen, Monika Tucholska, Hyungwon Choi, Anne-Claude Gingras, and Alexey I. Nesvizhskii. 2015. “DIA-Umpire: Comprehensive Computational Framework for Data-Independent Acquisition Proteomics.” Nature Methods 12 (3): 258–64. https://doi.org/10.1038/nmeth.3255.
Tsugawa, Hiroshi, Tomas Cajka, Tobias Kind, Yan Ma, Brendan Higgins, Kazutaka Ikeda, Mitsuhiro Kanazawa, Jean VanderGheynst, Oliver Fiehn, and Masanori Arita. 2015. “MS-DIAL: Data-Independent MS/MS Deconvolution for Comprehensive Metabolome Analysis.” Nature Methods 12 (6): 523–26. https://doi.org/10.1038/nmeth.3393.
Tsugawa, Hiroshi, Tobias Kind, Ryo Nakabayashi, Daichi Yukihira, Wataru Tanaka, Tomas Cajka, Kazuki Saito, Oliver Fiehn, and Masanori Arita. 2016. “Hydrogen Rearrangement Rules: Computational MS/MS Fragmentation and Structure Elucidation Using MS-FINDER Software.” Analytical Chemistry 88 (16): 7946–58. https://doi.org/10.1021/acs.analchem.6b00770.
Uchino, Haruki, Hiroshi Tsugawa, Hidenori Takahashi, and Makoto Arita. 2022. “Computational Mass Spectrometry Accelerates C = C Position-Resolved Untargeted Lipidomics Using Oxygen Attachment Dissociation.” Communications Chemistry 5 (1): 1–13. https://doi.org/10.1038/s42004-022-00778-1.
Uppal, Karan, Quinlyn A. Soltow, Frederick H. Strobel, W. Stephen Pittard, Kim M. Gernert, Tianwei Yu, and Dean P. Jones. 2013. “xMSanalyzer: Automated Pipeline for Improved Feature Detection and Downstream Analysis of Large-Scale, Non-Targeted Metabolomics Data.” BMC Bioinformatics 14 (1): 15. https://doi.org/10.1186/1471-2105-14-15.
Uppal, Karan, Douglas I. Walker, and Dean P. Jones. 2017. “xMSannotator: An R Package for Network-Based Annotation of High-Resolution Metabolomics Data.” Analytical Chemistry 89 (2): 1063–67. https://doi.org/10.1021/acs.analchem.6b01214.
Uppal, Karan, Douglas I. Walker, Ken Liu, Shuzhao Li, Young-Mi Go, and Dean P. Jones. 2016. “Computational Metabolomics: A Framework for the Million Metabolome.” Chemical Research in Toxicology 29 (12): 1956–75. https://doi.org/10.1021/acs.chemrestox.6b00179.
van der Kloet, Frans M., Ivana Bobeldijk, Elwin R. Verheij, and Renger H. Jellema. 2009. “Analytical Error Reduction Using Single Point Calibration for Accurate and Precise Metabolomic Phenotyping.” Journal of Proteome Research 8 (11): 5132–41. https://doi.org/10.1021/pr900499r.
van Tetering, Lara, Sylvia Spies, Quirine D. K. Wildeman, Kas J. Houthuijs, Rianne E. van Outersterp, Jonathan Martens, Ron A. Wevers, David S. Wishart, Giel Berden, and Jos Oomens. 2024. “A Spectroscopic Test Suggests That Fragment Ion Structure Annotations in MS/MS Libraries Are Frequently Incorrect.” Communications Chemistry 7 (1): 1–11. https://doi.org/10.1038/s42004-024-01112-7.
Verhoeven, Aswin, Martin Giera, and Oleg A. Mayboroda. 2020. “Scientific Workflow Managers in Metabolomics: An Overview.” Analyst 145 (11): 3801–8. https://doi.org/10.1039/D0AN00272K.
Viant, Mark R., Timothy M. D. Ebbels, Richard D. Beger, Drew R. Ekman, David J. T. Epps, Hennicke Kamp, Pim E. G. Leonards, et al. 2019. “Use Cases, Best Practice and Reporting Standards for Metabolomics in Regulatory Toxicology.” Nature Communications 10 (1): 3041. https://doi.org/10.1038/s41467-019-10900-y.
Viant, Mark R, Irwin J Kurland, Martin R Jones, and Warwick B Dunn. 2017. “How Close Are We to Complete Annotation of Metabolomes?” Current Opinion in Chemical Biology, Omics, 36 (February): 64–69. https://doi.org/10.1016/j.cbpa.2017.01.001.
Vinaixa, Maria, Emma L. Schymanski, Steffen Neumann, Miriam Navarro, Reza M. Salek, and Oscar Yanes. 2016. “Mass Spectral Databases for LC/MS- and GC/MS-based Metabolomics: State of the Field and Future Prospects.” TrAC Trends in Analytical Chemistry 78 (April): 23–35. https://doi.org/10.1016/j.trac.2015.09.005.
Vitale, Chiara Maria, Arjen Lommen, Carolin Huber, Kevin Wagner, Borja Garlito Molina, Rosalie Nijssen, Elliott James Price, et al. 2022. “Harmonized Quality Assurance/Quality Control Provisions for Nontargeted Measurement of Urinary Pesticide Biomarkers in the HBM4EU Multisite SPECIMEn Study.” Analytical Chemistry 94 (22): 7833–43. https://doi.org/10.1021/acs.analchem.2c00061.
Volikov, Alexander, Gleb Rukhovich, and Irina V. Perminova. 2023. “NOMspectra: An Open-Source Python Package for Processing High Resolution Mass Spectrometry Data on Natural Organic Matter.” NOMspectra: An Open-Source Python Package for Processing High Resolution Mass Spectrometry Data on Natural Organic Matter, June. https://doi.org/10.1021/jasms.3c00003.
Wallach, Joshua D., Kevin W. Boyack, and John P. A. Ioannidis. 2018. “Reproducible Research Practices, Transparency, and Open Access Data in the Biomedical Literature, 2015–2017.” PLOS Biology 16 (11): e2006930. https://doi.org/10.1371/journal.pbio.2006930.
Wandro, Stephen, Lisa Carmody, Tara Gallagher, John J. LiPuma, and Katrine Whiteson. 2017. “Making It Last: Storage Time and Temperature Have Differential Impacts on Metabolite Profiles of Airway Samples from Cystic Fibrosis Patients.” mSystems 2 (6). https://doi.org/10.1128/mSystems.00100-17.
Wang, Mingxun, Jeremy J. Carver, Vanessa V. Phelan, Laura M. Sanchez, Neha Garg, Yao Peng, Don Duy Nguyen, et al. 2016. “Sharing and Community Curation of Mass Spectrometry Data with Global Natural Products Social Molecular Networking.” Nature Biotechnology 34 (8): 828–37. https://doi.org/10.1038/nbt.3597.
Wang, Ruimin, Miaoshan Lu, Shaowei An, Jinyin Wang, and Changbin Yu. 2023. “G-Aligner: A Graph-Based Feature Alignment Method for Untargeted LC–MS-based Metabolomics.” BMC Bioinformatics 24 (1): 431. https://doi.org/10.1186/s12859-023-05525-4.
Wang, Ruohong, Yandong Yin, and Zheng-Jiang Zhu. 2019. “Advancing Untargeted Metabolomics Using Data-Independent Acquisition Mass Spectrometry Technology.” Analytical and Bioanalytical Chemistry 411 (19): 4349–57. https://doi.org/10.1007/s00216-019-01709-1.
Wang, San-Yuan, Ching-Hua Kuo, and Yufeng J. Tseng. 2013. “Batch Normalizer: A Fast Total Abundance Regression Calibration Method to Simultaneously Adjust Batch and Injection Order Effects in Liquid Chromatography/Time-of-Flight Mass Spectrometry-Based Metabolomics Data and Comparison with Current Calibration Methods.” Analytical Chemistry 85 (2): 1037–46. https://doi.org/10.1021/ac302877x.
Wang, Suping, Xiaojuan Jiang, Rong Ding, Binbin Chen, Haiyan Lyu, Junyang Liu, Chunyan Zhu, et al. 2022. “MS-IDF: A Software Tool for Nontargeted Identification of Endogenous Metabolites After Chemical Isotope Labeling Based on a Narrow Mass Defect Filter.” Analytical Chemistry 94 (7): 3194–3202. https://doi.org/10.1021/acs.analchem.1c04719.
Wang, Yang, Fang Liu, Peng Li, Chengwei He, Ruibing Wang, Huanxing Su, and Jian-Bo Wan. 2016. “An Improved Pseudotargeted Metabolomics Approach Using Multiple Ion Monitoring with Time-Staggered Ion Lists Based on Ultra-High Performance Liquid Chromatography/Quadrupole Time-of-Flight Mass Spectrometry.” Analytica Chimica Acta 927 (July): 82–88. https://doi.org/10.1016/j.aca.2016.05.008.
Warth, Benedikt, Scott Spangler, Mingliang Fang, Caroline H. Johnson, Erica M. Forsberg, Ana Granados, Richard L. Martin, et al. 2017. “Exposome-Scale Investigations Guided by Global Metabolomics, Pathway Analysis, and Cognitive Computing.” Analytical Chemistry 89 (21): 11505–13. https://doi.org/10.1021/acs.analchem.7b02759.
Weber, Ralf J. M., Thomas N. Lawson, Reza M. Salek, Timothy M. D. Ebbels, Robert C. Glen, Royston Goodacre, Julian L. Griffin, et al. 2017. “Computational Tools and Workflows in Metabolomics: An International Survey Highlights the Opportunity for Harmonisation Through Galaxy.” Metabolomics 13 (2). https://doi.org/10.1007/s11306-016-1147-x.
Weber, Ralf J. M., and Mark R. Viant. 2010. “MI-Pack: Increased Confidence of Metabolite Identification in Mass Spectra by Integrating Accurate Masses and Metabolic Pathways.” Chemometrics and Intelligent Laboratory Systems, OMICS, 104 (1): 75–82. https://doi.org/10.1016/j.chemolab.2010.04.010.
Wehrens, Ron, Tom G. Bloemberg, and Paul H. C. Eilers. 2015. “Fast Parametric Time Warping of Peak Lists.” Bioinformatics 31 (18): 3063–65. https://doi.org/10.1093/bioinformatics/btv299.
Wei, Runmin, Jingye Wang, Mingming Su, Erik Jia, Shaoqiu Chen, Tianlu Chen, and Yan Ni. 2018. “Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data.” Scientific Reports 8 (1): 663. https://doi.org/10.1038/s41598-017-19120-0.
Weljie, Aalim M., Jack Newton, Pascal Mercier, Erin Carlson, and Carolyn M. Slupsky. 2006. “Targeted Profiling: Quantitative Analysis of 1H NMR Metabolomics Data.” Analytical Chemistry 78 (13): 4430–42. https://doi.org/10.1021/ac060209g.
Wen, Bo, Zhanlong Mei, Chunwei Zeng, and Siqi Liu. 2017. “metaX: A Flexible and Comprehensive Software for Processing Metabolomics Data.” BMC Bioinformatics 18 (March): 183. https://doi.org/10.1186/s12859-017-1579-y.
Wiklund, Susanne, Erik Johansson, Lina Sjöström, Ewa J. Mellerowicz, Ulf Edlund, John P. Shockcor, Johan Gottfries, Thomas Moritz, and Johan Trygg. 2008. “Visualization of GC/TOF-MS-Based Metabolomics Data for Identification of Biochemically Interesting Compounds Using OPLS Class Models.” Analytical Chemistry 80 (1): 115–22. https://doi.org/10.1021/ac0713510.
Wise, Stephen A. 2022. “What If Using Certified Reference Materials (CRMs) Was a Requirement to Publish in Analytical/Bioanalytical Chemistry Journals?” Analytical and Bioanalytical Chemistry 414 (24): 7015–22. https://doi.org/10.1007/s00216-022-04163-8.
Wishart, David S. 2016. “Emerging Applications of Metabolomics in Drug Discovery and Precision Medicine.” Nature Reviews Drug Discovery 15 (7): 473–84. https://doi.org/10.1038/nrd.2016.32.
Witting, Michael, Christoph Ruttkies, Steffen Neumann, and Philippe Schmitt-Kopplin. 2017. “LipidFrag: Improving Reliability of in Silico Fragmentation of Lipids and Application to the Caenorhabditis Elegans Lipidome.” PLOS ONE 12 (3): e0172311. https://doi.org/10.1371/journal.pone.0172311.
Wolf, Sebastian, Stephan Schmidt, Matthias Müller-Hannemann, and Steffen Neumann. 2010. “In Silico Fragmentation for Computer Assisted Identification of Metabolite Mass Spectra.” BMC Bioinformatics 11 (March): 148. https://doi.org/10.1186/1471-2105-11-148.
Wolfender, Jean-Luc, Guillaume Marti, Aurélien Thomas, and Samuel Bertrand. 2015. “Current Approaches and Challenges for the Metabolite Profiling of Complex Natural Extracts.” Journal of Chromatography A, Editors’ Choice IX, 1382 (February): 136–64. https://doi.org/10.1016/j.chroma.2014.10.091.
Wright, Elliott J., Daniel G. Beach, and Pearse McCarron. 2022. “Non-Target Analysis and Stability Assessment of Reference Materials Using Liquid Chromatography-High-Resolution Mass Spectrometry.” Analytica Chimica Acta 1201 (April): 339622. https://doi.org/10.1016/j.aca.2022.339622.
Wu, Yiman, and Liang Li. 2016. “Sample Normalization Methods in Quantitative Metabolomics.” Journal of Chromatography A, Editors’ Choice X, 1430 (January): 80–95. https://doi.org/10.1016/j.chroma.2015.12.007.
Xing, Shipei, Sam Shen, Banghua Xu, Xiaoxiao Li, and Tao Huan. 2023. “BUDDY: Molecular Formula Discovery via Bottom-up MS/MS Interrogation.” Nature Methods, April, 1–10. https://doi.org/10.1038/s41592-023-01850-x.
Xu, Yi-Fan, Wenyun Lu, and Joshua D. Rabinowitz. 2015. “Avoiding Misannotation of In-Source Fragmentation Products as Cellular Metabolites in Liquid Chromatography–Mass Spectrometry-Based Metabolomics.” Analytical Chemistry 87 (4): 2273–81. https://doi.org/10.1021/ac504118y.
Xue, Jingchuan, Rico J. E. Derks, Bill Webb, Elizabeth M. Billings, Aries Aisporna, Martin Giera, and Gary Siuzdak. 2021. “Single Quadrupole Multiple Fragment Ion Monitoring Quantitative Mass Spectrometry.” Analytical Chemistry 93 (31): 10879–89. https://doi.org/10.1021/acs.analchem.1c01246.
Xue, Jingchuan, Xavier Domingo-Almenara, Carlos Guijas, Amelia Palermo, Markus M. Rinschen, John Isbell, H. Paul Benton, and Gary Siuzdak. 2020. “Enhanced in-Source Fragmentation Annotation Enables Novel Data Independent Acquisition and Autonomous METLIN Molecular Identification.” Analytical Chemistry 92 (8): 6051–59. https://doi.org/10.1021/acs.analchem.0c00409.
Xue, Jingchuan, Carlos Guijas, H. Paul Benton, Benedikt Warth, and Gary Siuzdak. 2020. “METLIN MS 2 Molecular Standards Database: A Broad Chemical and Biological Resource.” Nature Methods 17 (10): 953–54. https://doi.org/10.1038/s41592-020-0942-5.
Xue, Jingchuan, Jiamin Zhu, Lixin Hu, Junjie Yang, Yunbo Lv, Fanrong Zhao, Yuxian Liu, Tao Zhang, Yanpeng Cai, and Mingliang Fang. 2023. “EISA-EXPOSOME: One Highly Sensitive and Autonomous Exposomic Platform with Enhanced in-Source Fragmentation/Annotation.” Analytical Chemistry, November. https://doi.org/10.1021/acs.analchem.3c02697.
Yamamoto, Hiroyuki, Tamaki Fujimori, Hajime Sato, Gen Ishikawa, Kenjiro Kami, and Yoshiaki Ohashi. 2014. “Statistical Hypothesis Testing of Factor Loading in Principal Component Analysis and Its Application to Metabolite Set Enrichment Analysis.” BMC Bioinformatics 15 (February): 51. https://doi.org/10.1186/1471-2105-15-51.
Yan, Binjun, Mengtian Shi, Siyu Cai, Yuan Su, Renhui Chen, Chiyuan Huang, and David Da Yong Chen. 2023. “Data-Driven Tool for Cross-Run Ion Selection and Peak-Picking in Quantitative Proteomics with Data-Independent Acquisition LC–MS/MS.” Analytical Chemistry 95 (45): 16558–66. https://doi.org/10.1021/acs.analchem.3c02689.
Yang, Qingxia, Yunxia Wang, Ying Zhang, Fengcheng Li, Weiqi Xia, Ying Zhou, Yunqing Qiu, Honglin Li, and Feng Zhu. 2020. “NOREVA: Enhanced Normalization and Evaluation of Time-Course and Multi-Class Metabolomic Data.” Nucleic Acids Research 48 (W1): W436–48. https://doi.org/10.1093/nar/gkaa258.
Yang, Qin, Shan-Shan Lin, Jiang-Tao Yang, Li-Juan Tang, and Ru-Qin Yu. 2017. “Detection of Inborn Errors of Metabolism Utilizing GC-MS Urinary Metabolomics Coupled with a Modified Orthogonal Partial Least Squares Discriminant Analysis.” Talanta 165 (April): 545–52. https://doi.org/10.1016/j.talanta.2017.01.018.
Yang, Qiong, Hongchao Ji, Zhenbo Xu, Yiming Li, Pingshan Wang, Jinyu Sun, Xiaqiong Fan, Hailiang Zhang, Hongmei Lu, and Zhimin Zhang. 2023. “Ultra-Fast and Accurate Electron Ionization Mass Spectrum Matching for Compound Identification with Million-Scale in-Silico Library.” Nature Communications 14 (1): 3722. https://doi.org/10.1038/s41467-023-39279-7.
Yang, Ruochen, Xi Chen, and Idoia Ochoa. 2019. “MassComp, a Lossless Compressor for Mass Spectrometry Data.” BMC Bioinformatics 20 (1): 368. https://doi.org/10.1186/s12859-019-2962-7.
Yates Iii, John R. 2011. “A Century of Mass Spectrometry: From Atoms to Proteomes.” Nature Methods 8 (8): 633–37. https://doi.org/10.1038/nmeth.1659.
Yu, Miao, Georgia Dolios, and Lauren Petrick. 2022. “Reproducible Untargeted Metabolomics Workflow for Exhaustive MS2 Data Acquisition of MS1 Features.” Journal of Cheminformatics 14 (1): 6. https://doi.org/10.1186/s13321-022-00586-8.
Yu, Miao, Sofia Lendor, Anna Roszkowska, Mariola Olkowicz, Leslie Bragg, Mark Servos, and Janusz Pawliszyn. 2020. “Metabolic Profile of Fish Muscle Tissue Changes with Sampling Method, Storage Strategy and Time.” Analytica Chimica Acta 1136 (November): 42–50. https://doi.org/10.1016/j.aca.2020.08.050.
Yu, Miao, Mariola Olkowicz, and Janusz Pawliszyn. 2019. “Structure/Reaction Directed Analysis for LC-MS Based Untargeted Analysis.” Analytica Chimica Acta 1050 (March): 16–24. https://doi.org/10.1016/j.aca.2018.10.062.
Yu, Miao, Susan L. Teitelbaum, Georgia Dolios, Lam-Ha T. Dang, Peijun Tu, Mary S. Wolff, and Lauren M. Petrick. 2022. “Molecular Gatekeeper Discovery: Workflow for Linking Multiple Exposure Biomarkers to Metabolomics.” Environmental Science & Technology 56 (10): 6162–71. https://doi.org/10.1021/acs.est.1c04039.
Yu, Tianwei, Youngja Park, Jennifer M. Johnson, and Dean P. Jones. 2009. “apLCMS—Adaptive Processing of High-Resolution LC/MS Data.” Bioinformatics 25 (15): 1930–36. https://doi.org/10.1093/bioinformatics/btp291.
Yu, Yong-Jie, Qing-Xia Zheng, Yue-Ming Zhang, Qian Zhang, Yu-Ying Zhang, Ping-Ping Liu, Peng Lu, et al. 2019. “Automatic Data Analysis Workflow for Ultra-High Performance Liquid Chromatography-High Resolution Mass Spectrometry-Based Metabolomics.” Journal of Chromatography A 1585 (January): 172–81. https://doi.org/10.1016/j.chroma.2018.11.070.
Yu, Zhihao, Haylea C. Miller, Geoffrey J. Puzon, and Brian H. Clowers. 2017. “Development of Untargeted Metabolomics Methods for the Rapid Detection of Pathogenic Naegleria Fowleri.” Environmental Science & Technology 51 (8): 4210–19. https://doi.org/10.1021/acs.est.6b05969.
Yuan, Min, Susanne B. Breitkopf, Xuemei Yang, and John M. Asara. 2012. “A Positive/Negative Ion–Switching, Targeted Mass Spectrometry–Based Metabolomics Platform for Bodily Fluids, Cells, and Fresh and Fixed Tissue.” Nature Protocols 7 (5): 872–81. https://doi.org/10.1038/nprot.2012.024.
Zenobi, R. 2013. “Single-Cell Metabolomics: Analytical and Biological Perspectives.” Science 342 (6163): 1243259. https://doi.org/10.1126/science.1243259.
Zha, Haihong, Yuping Cai, Yandong Yin, Zhuozhong Wang, Kang Li, and Zheng-Jiang Zhu. 2018. “SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery.” Analytical Chemistry 90 (6): 4062–70. https://doi.org/10.1021/acs.analchem.7b05318.
Zhang, Aihua, Hui Sun, Ping Wang, Ying Han, and Xijun Wang. 2012. “Modern Analytical Techniques in Metabolomics Analysis.” The Analyst 137 (2): 293–300. https://doi.org/10.1039/C1AN15605E.
Zhang, Xiuqiong, Zaifang Li, Chunxia Zhao, Tiantian Chen, Xinxin Wang, Xiaoshan Sun, Xinjie Zhao, Xin Lu, and Guowang Xu. 2024. “Leveraging Unidentified Metabolic Features for Key Pathway Discovery: Chemical Classification-driven Network Analysis in Untargeted Metabolomics.” Analytical Chemistry, February. https://doi.org/10.1021/acs.analchem.3c04591.
Zhang, Yuhao, Jingyu Liao, Wanqi Le, Gaosong Wu, and Weidong Zhang. 2023. “Improving the Data Quality of Untargeted Metabolomics Through a Targeted Data-Dependent Acquisition Based on an Inclusion List of Differential and Preidentified Ions.” Analytical Chemistry 95 (34): 12964–73. https://doi.org/10.1021/acs.analchem.3c02888.
Zhang, Yu-Ying, Qian Zhang, Yue-Ming Zhang, Wei-Wei Wang, Li Zhang, Yong-Jie Yu, Chang-Cai Bai, Ji-Zhao Guo, Hai-Yan Fu, and Yuanbin She. 2020. “A Comprehensive Automatic Data Analysis Strategy for Gas Chromatography-Mass Spectrometry Based Untargeted Metabolomics.” Journal of Chromatography A 1616 (April): 460787. https://doi.org/10.1016/j.chroma.2019.460787.
Zhang, Zixuan, Huaxu Yu, Ethan Wong-Ma, Pouneh Dokouhaki, Ahmed Mostafa, Jay S. Shavadia, Fang Wu, and Tao Huan. 2024. “Reducing Quantitative Uncertainty Caused by Data Processing in Untargeted Metabolomics.” Analytical Chemistry 96 (9): 3727–32. https://doi.org/10.1021/acs.analchem.3c04046.
Zhao, Fan, Shuai Huang, and Xiaozhe Zhang. 2021. “High Sensitivity and Specificity Feature Detection in Liquid Chromatography–Mass Spectrometry Data: A Deep Learning Framework.” Talanta 222 (January): 121580. https://doi.org/10.1016/j.talanta.2020.121580.
Zhao, Shuang, and Liang Li. 2020. “Chemical Derivatization in LC-MS-based Metabolomics Study.” TrAC Trends in Analytical Chemistry 131 (October): 115988. https://doi.org/10.1016/j.trac.2020.115988.
Zhao, Tingting, Shipei Xing, Huaxu Yu, and Tao Huan. 2023. “De Novo Cleaning of Chimeric MS/MS Spectra for LC-MS/MS-Based Metabolomics.” Analytical Chemistry 95 (35): 13018–28. https://doi.org/10.1021/acs.analchem.3c00736.
Zheng, Fujian, Lei You, Wangshu Qin, Runze Ouyang, Wangjie Lv, Lei Guo, Xin Lu, Enyou Li, Xinjie Zhao, and Guowang Xu. 2022. “MetEx: A Targeted Extraction Strategy for Improving the Coverage and Accuracy of Metabolite Annotation in Liquid Chromatography–High-Resolution Mass Spectrometry Data.” Analytical Chemistry 94 (24): 8561–69. https://doi.org/10.1021/acs.analchem.1c04783.
Zheng, Fujian, Xinjie Zhao, Zhongda Zeng, Lichao Wang, Wangjie Lv, Qingqing Wang, and Guowang Xu. 2020. “Development of a Plasma Pseudotargeted Metabolomics Method Based on Ultra-High-Performance Liquid Chromatography–Mass Spectrometry.” Nature Protocols 15 (8): 2519–37. https://doi.org/10.1038/s41596-020-0341-5.
Zhou, Juntuo, and Yuxin Yin. 2016. “Strategies for Large-Scale Targeted Metabolomics Quantification by Liquid Chromatography-Mass Spectrometry.” Analyst 141 (23): 6362–73. https://doi.org/10.1039/C6AN01753C.
Zhou, Zhiwei, Mingdu Luo, Haosong Zhang, Yandong Yin, Yuping Cai, and Zheng-Jiang Zhu. 2022. “Metabolite Annotation from Knowns to Unknowns Through Knowledge-Guided Multi-Layer Metabolic Networking.” Nature Communications 13 (1): 6656. https://doi.org/10.1038/s41467-022-34537-6.
Zhu, Xiaochun, Yuping Chen, and Raju Subramanian. 2014. “Comparison of Information-Dependent Acquisition, SWATH, and MSAll Techniques in Metabolite Identification Study Employing Ultrahigh-Performance Liquid Chromatography–Quadrupole Time-of-Flight Mass Spectrometry.” Analytical Chemistry 86 (2): 1202–9. https://doi.org/10.1021/ac403385y.
Zubeldia-Varela, Elisa, Domingo Barber, Coral Barbas, Marina Perez-Gordo, and David Rojo. 2020. “Sample Pre-Treatment Procedures for the Omics Analysis of Human Gut Microbiota: Turning Points, Tips and Tricks for Gene Sequencing and Metabolomics.” Journal of Pharmaceutical and Biomedical Analysis 191 (November): 113592. https://doi.org/10.1016/j.jpba.2020.113592.