A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

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Proposed minimum reporting standards for chemical analysis: Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI)

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Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking

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MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis

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The re-emergence of natural products for drug discovery in the genomics era

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MassBank: a public repository for sharing mass spectral data for life sciences

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Drought, salt, and temperature stress-induced metabolic rearrangements and regulatory networks

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ClassyFire: automated chemical classification with a comprehensive, computable taxonomy

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METLIN: A Technology Platform for Identifying Knowns and Unknowns

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The future of NMR-based metabolomics

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PAGE: Parametric Analysis of Gene Set Enrichment

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Hydrogen Rearrangement Rules: Computational MS/MS Fragmentation and Structure Elucidation Using MS-FINDER Software

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Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics

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Increased Permeability of the Aquaporin SoPIP2;1 by Mercury and Mutations in Loop A

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RIKEN tandem mass spectral database (ReSpect) for phytochemicals: A plant-specific MS/MS-based data resource and database

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Elemental formula annotation of polar and lipophilic metabolites using 13 C, 15 N and 34 S isotope labelling, in combination with high‐resolution mass spectrometry

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Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites

Mahieu, N. G., & Patti, G. J. (2017) · Analytical Chemistry · doi:10.1021/acs.analchem.7b02380 · Cited by 321 · see citing works

Super Natural II—a database of natural products

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Stable Isotope-Labeling Studies in Metabolomics: New Insights Into Structure and Dynamics of Metabolic Networks

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Development and Performance of a Gas Chromatography−Time-of-Flight Mass Spectrometry Analysis for Large-Scale Nontargeted Metabolomic Studies of Human Serum

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Significance estimation for large scale metabolomics annotations by spectral matching

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Annotation: A Computational Solution for Streamlining Metabolomics Analysis

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Feasible production of camptothecin by hairy root culture of Ophiorrhiza pumila

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A novel applicability domain technique for mapping predictive reliability across the chemical space of a QSAR: reliability-density neighbourhood

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Exposome-Scale Investigations Guided by Global Metabolomics, Pathway Analysis, and Cognitive Computing

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Systematic Structural Characterization of Metabolites in Arabidopsis via Candidate Substrate-Product Pair Networks

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Advances in computational metabolomics and databases deepen the understanding of metabolisms

Tsugawa, H. (2018) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2018.01.008 · Cited by 97 · see citing works

Genome-wide association mapping of growth dynamics detects time-specific and general quantitative trait loci

Bac-Molenaar, J. A., Vreugdenhil, D., Granier, C., & Keurentjes, J. J. B. (2015) · Journal of Experimental Botany · doi:10.1093/jxb/erv176 · Cited by 84 · see citing works

Genome‐wide association mapping of time‐dependent growth responses to moderate drought stress in Arabidopsis

Bac-Molenaar, J. A., Granier, C., Keurentjes, J. J. B., & Vreugdenhil, D. (2015) · Plant Cell & Environment · doi:10.1111/pce.12595 · Cited by 80 · see citing works

A Spectral Clustering Approach to MS/MS Identification of Post-Translational Modifications

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Combination of Liquid Chromatography–Fourier Transform Ion Cyclotron Resonance-Mass Spectrometry with 13C-Labeling for Chemical Assignment of Sulfur-Containing Metabolites in Onion Bulbs

Nakabayashi, R., Sawada, Y., Yamada, Y., Suzuki, M., Hirai, M. Y., Sakurai, T., & Saito, K. (2013) · Analytical Chemistry · doi:10.1021/ac302733c · Cited by 77 · see citing works

Function of AP2/ERF Transcription Factors Involved in the Regulation of Specialized Metabolism in Ophiorrhiza pumila Revealed by Transcriptomics and Metabolomics

Udomsom, N., Rai, A., Suzuki, H., Okuyama, J., Imai, R., Mori, T., Nakabayashi, R., Saito, K., & Yamazaki, M. (2016) · Frontiers in Plant Science · doi:10.3389/fpls.2016.01861 · Cited by 75 · see citing works

Genome-Wide Association Mapping and Genomic Prediction Elucidate the Genetic Architecture of Morphological Traits in Arabidopsis

Kooke, R., Kruijer, W., Bours, R., Becker, F. F. M., Kuhn, A., van de Geest, H., Buntjer, J. B., Doeswijk, T. G., Guerra, J., Bouwmeester, H. J., et al. (2016) · PLANT PHYSIOLOGY · doi:10.1104/pp.15.00997 · Cited by 73 · see citing works

PlantMAT: A Metabolomics Tool for Predicting the Specialized Metabolic Potential of a System and for Large-Scale Metabolite Identifications

Qiu, F., Fine, D. D., Wherritt, D., Lei, Z., & Sumner, L. W. (2016) · Analytical Chemistry · doi:10.1021/acs.analchem.6b00906 · Cited by 60 · see citing works

A Novel Amino Acid Glycoside and Three Amino Acids from Allium sativum

Mütsch-Eckner, M. C. V., Erdelmeier, C. A. J., Sticher, O., & Reuter, H. D. (1993) · Journal of Natural Products · doi:10.1021/np50096a009 · Cited by 26 · see citing works

The importance of bioinformatics for connecting data-driven lipidomics and biological insights

Tsugawa, H., Ikeda, K., & Arita, M. (2017) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2017.05.006 · Cited by 24 · see citing works

Glutathione S-Transferase π-Activatable O2-(Sulfonylethyl Derived) Diazeniumdiolates Potently Suppress Melanoma in Vitro and in Vivo

Huang, Z., Wu, J., Zou, Y. S., Yuan, H., Zhang, Y., Fei, Y., Bhardwaj, A., Kaur, J. P., Knaus, E. E., & Zhang, Y. (2018) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.7b01178 · Cited by 17 · see citing works

Liquid chromatography–tandem mass spectrometry of phosphatidylserine advanced glycated end products

Maciel, E. A., da Silva, R. N., Simões, C. S. O., Melo, T., Ferreira, R. M., Domingues, P. M., & Domingues, M. R. (2013) · Chemistry and Physics of Lipids · doi:10.1016/j.chemphyslip.2013.05.005 · Cited by 12 · see citing works

MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation

Pang, Z., Lu, Y. P., Zhou, G., Hui, F., Xu, L., Viau, C., Spigelman, A. F., MacDonald, P. E., Wishart, D. S., Li, S., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae253 · Cited by 2,373 · see citing works

Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices

Alseekh, S., Aharoni, A., Brotman, Y., Contrepois, K., D’Auria, J. C., Ewald, J., Ewald, J. C., Fraser, P. D., Giavalisco, P., Hall, R. D., et al. (2021) · Nature Methods · doi:10.1038/s41592-021-01197-1 · Cited by 1,151 · see citing works

A lipidome atlas in MS-DIAL 4

Tsugawa, H., Ikeda, K., Takahashi, M., Satoh, A., Mori, Y., Uchino, H., Okahashi, N., Yamada, Y., Tada, I., Bonini, P., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0531-2 · Cited by 895 · see citing works

Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra

Dührkop, K., Nothias, L.-F., Fleischauer, M., Reher, R., Ludwig, M., Hoffmann, M. A., Petras, D., Gerwick, W. H., Rousu, J., Dorrestein, P. C., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-0740-8 · Cited by 860 · see citing works

The Origin and Evolution of Plant Flavonoid Metabolism

Yonekura‐Sakakibara, K., Higashi, Y., & Nakabayashi, R. (2019) · Frontiers in Plant Science · doi:10.3389/fpls.2019.00943 · Cited by 486 · see citing works

Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment

Schmid, R., Petras, D., Nothias-Scaglia, L.-F., Wang, M., Aron, A. T., Jagels, A., Tsugawa, H., Rainer, J., Garcia‐Aloy, M., Dührkop, K., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23953-9 · Cited by 356 · see citing works

Metabolite annotation from knowns to unknowns through knowledge-guided multi-layer metabolic networking

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Metabolite discovery through global annotation of untargeted metabolomics data

Chen, L., Lu, W., Wang, L., Xing, X., Chen, Z., Teng, X., Zeng, X., Muscarella, A. D., Shen, Y., Cowan, A. J., et al. (2021) · Nature Methods · doi:10.1038/s41592-021-01303-3 · Cited by 259 · see citing works

Retip: Retention Time Prediction for Compound Annotation in Untargeted Metabolomics

Bonini, P., Kind, T., Tsugawa, H., Barupal, D. K., & Fiehn, O. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.9b05765 · Cited by 251 · see citing works

Intestinal microbiota-derived tryptophan metabolites are predictive of Ah receptor activity

Dong, F., Hao, F., Murray, I. A., Smith, P. B. W., Koo, I., Tindall, A. M., Kris‐Etherton, P. M., Gowda, K., Amin, S., Patterson, A. D., et al. (2020) · Gut Microbes · doi:10.1080/19490976.2020.1788899 · Cited by 252 · see citing works

Recurrent Topics in Mass Spectrometry-Based Metabolomics and Lipidomics─Standardization, Coverage, and Throughput

Rampler, E., Abiead, Y. E., Schoeny, H., Rusz, M., Hildebrand, F., Fitz, V., & Koellensperger, G. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.0c04698 · Cited by 171 · see citing works

Lipidomic studies of membrane glycerolipids in plant leaves under heat stress

Higashi, Y., & Saito, K. (2019) · Progress in Lipid Research · doi:10.1016/j.plipres.2019.100990 · Cited by 168 · see citing works

MS-DIAL 5 multimodal mass spectrometry data mining unveils lipidome complexities

Takeda, H., Matsuzawa, Y., Takeuchi, M., Takahashi, M., Nishida, K., 原山, 武., Todoroki, Y., Shimizu, K., Sakamoto, N., Oka, T., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-54137-w · Cited by 138 · see citing works

Taxonomically Informed Scoring Enhances Confidence in Natural Products Annotation

Rutz, A., Dounoue-Kubo, M., Ollivier, S., Bisson, J. I., Bagheri, M., Saesong, T., Ebrahimi, S. N., Ingkaninan, K., Wolfender, J., & Allard, P. (2019) · Frontiers in Plant Science · doi:10.3389/fpls.2019.01329 · Cited by 134 · see citing works

The Roles of Functional Amino Acids in Plant Growth and Development

Kawade, K., Tabeta, H., Ferjani, A., & Hirai, M. Y. (2023) · Plant and Cell Physiology · doi:10.1093/pcp/pcad071 · Cited by 140 · see citing works

Chromosome-level genome assembly of Ophiorrhiza pumila reveals the evolution of camptothecin biosynthesis

Rai, A., Hirakawa, H., Nakabayashi, R., Kikuchi, S., Hayashi, K., Rai, M., Tsugawa, H., Nakaya, T., Mori, T., Nagasaki, H., et al. (2021) · Nature Communications · doi:10.1038/s41467-020-20508-2 · Cited by 132 · see citing works

MS-CleanR: A Feature-Filtering Workflow for Untargeted LC–MS Based Metabolomics

Fraisier, O., Chervin, J., Cabanac, G., Puech‐Pagès, V., Fournier, S., Durand, V., Amiel, A., André, O., Benamar, O. A., Dumas, B., et al. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.0c01594 · Cited by 119 · see citing works

Retrograde sulfur flow from glucosinolates to cysteine in Arabidopsis thaliana

Sugiyama, R., Li, R., Kuwahara, A., Nakabayashi, R., Sotta, N., Mori, T., Ito, T., Ohkama‐Ohtsu, N., Fujiwara, T., Saito, K., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2017890118 · Cited by 115 · see citing works

Metabolomics and complementary techniques to investigate the plant phytochemical cosmos

Tsugawa, H., Rai, A., Saito, K., & Nakabayashi, R. (2021) · Natural Product Reports · doi:10.1039/d1np00014d · Cited by 116 · see citing works

Next-Generation Mass Spectrometry Metabolomics Revives the Functional Analysis of Plant Metabolic Diversity

Li, D., & Gaquerel, E. (2021) · Annual Review of Plant Biology · doi:10.1146/annurev-arplant-071720-114836 · Cited by 102 · see citing works

Advanced analytical and informatic strategies for metabolite annotation in untargeted metabolomics

Cai, Y. A., Zhou, Z., & Zhu, Z. (2022) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2022.116903 · Cited by 104 · see citing works

The spatio‐temporal biosynthesis of floral flavonols is controlled by differential phylogenetic MYB regulators in Freesia hybrida

Shan, X., Li, Y., Song, Y., Yang, Z., Qiu, M., Gao, R., Han, T., Meng, X., Xu, Z., Wang, L., et al. (2020) · New Phytologist · doi:10.1111/nph.16818 · Cited by 96 · see citing works

Current Challenges and Recent Developments in Mass Spectrometry–Based Metabolomics

Collins, S. L., Koo, I., Peters, J. M., Smith, P. B. W., & Patterson, A. D. (2021) · Annual Review of Analytical Chemistry · doi:10.1146/annurev-anchem-091620-015205 · Cited by 92 · see citing works

Characterization of lipid profiling in three parts (muscle, head and viscera) of tilapia (Oreochromis niloticus) using lipidomics with UPLC-ESI-Q-TOF-MS

He, C., Cao, J., Bao, Y., Sun, Z., Liu, Z., & Li, C. (2021) · Food Chemistry · doi:10.1016/j.foodchem.2021.129057 · Cited by 79 · see citing works

Characterization of Lipid Profiles after Dietary Intake of Polyunsaturated Fatty Acids Using Integrated Untargeted and Targeted Lipidomics

Naoe, S., Tsugawa, H., Takahashi, M., Ikeda, K., & Arita, M. (2019) · Metabolites · doi:10.3390/metabo9100241 · Cited by 71 · see citing works

Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence Analyses

Yasuda, S., Okahashi, N., Tsugawa, H., Ogata, Y., Ikeda, K., Suda, W., Arai, H., Hattori, M., & Arita, M. (2020) · iScience · doi:10.1016/j.isci.2020.101841 · Cited by 69 · see citing works

Addressing big data challenges in mass spectrometry-based metabolomics

Guo, J. P., Yu, H., Xing, S., & Huan, T. (2022) · Chemical Communications · doi:10.1039/d2cc03598g · Cited by 69 · see citing works

Connecting metabolome and phenotype: recent advances in functional metabolomics tools for the identification of bioactive natural products

Vitale, G. A., Geibel, C., Minda, V., Wang, M., Aron, A. T., & Petras, D. (2024) · Natural Product Reports · doi:10.1039/d3np00050h · Cited by 66 · see citing works

Inducing secondary metabolite production of Aspergillus sydowii through microbial co-culture with Bacillus subtilis

Sun, Y., Liu, W., Shi, X., Zheng, H., Zheng, Z., Lu, X., Xing, Y., Ji, K., Liu, M., & Dong, Y. (2021) · Microbial Cell Factories · doi:10.1186/s12934-021-01527-0 · Cited by 62 · see citing works

Correlation-Based Deconvolution (CorrDec) To Generate High-Quality MS2 Spectra from Data-Independent Acquisition in Multisample Studies

Tada, I., Chaleckis, R., Tsugawa, H., Meister, I., Zhang, P., Lazarinis, N., Dahlén, B., Wheelock, C. E., & Arita, M. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.0c01980 · Cited by 59 · see citing works

Genome-wide characterization of 2-oxoglutarate and Fe(II)-dependent dioxygenase family genes in tomato during growth cycle and their roles in metabolism

Wei, S., Zhang, W., Fu, R., & Zhang, Y. (2021) · BMC Genomics · doi:10.1186/s12864-021-07434-3 · Cited by 59 · see citing works

Comprehensive profiling of phenolic compounds by HPLC-DAD-ESI-QTOF-MS/MS to reveal their location and form of presence in different sorghum grain genotypes

Xiong, Y., Zhang, P., Warner, R. D., Shen, S., Johnson, S. K., & Fang, Z. (2020) · Food Research International · doi:10.1016/j.foodres.2020.109671 · Cited by 59 · see citing works

Graph Convolutional Networks for Improved Prediction and Interpretability of Chromatographic Retention Data

Kensert, A., Bouwmeester, R., Efthymiadis, K., Broeck, P. V., Desmet, G., & Cabooter, D. (2021) · Analytical Chemistry · doi:10.1021/acs.analchem.1c02988 · Cited by 56 · see citing works

High-Precision Automated Workflow for Urinary Untargeted Metabolomic Epidemiology

Meister, I., Zhang, P., Sinha, A., Sköld, C. M., Wheelock, Å. M., Izumi, T., Chaleckis, R., & Wheelock, C. E. (2021) · Analytical Chemistry · doi:10.1021/acs.analchem.1c00203 · Cited by 55 · see citing works

Machine learning-assisted structure annotation of natural products based on MS and NMR data

Hu, G., & Qiu, M. (2023) · Natural Product Reports · doi:10.1039/d3np00025g · Cited by 54 · see citing works

Chemical Profiling, Antioxidant, Cytotoxic Activities and Molecular Docking Simulation of Carrichtera annua DC. (Cruciferae)

Eltamany, E. E., Elhady, S. S., Ahmed, H. A., Badr, J. M., Noor, A. O., Ahmed, S. A., & Nafie, M. S. (2020) · Antioxidants · doi:10.3390/antiox9121286 · Cited by 53 · see citing works

A Genetic and Metabolomic Perspective on the Production of Indole-3-Acetic Acid by Pantoea agglomerans and Use of Their Metabolites as Biostimulants in Plant Nurseries

Luziatelli, F., Ficca, A. G., Bonini, P., Muleo, R., Gatti, L., Meneghini, M., Tronati, M., Melini, F., & Ruzzi, M. (2020) · Frontiers in Microbiology · doi:10.3389/fmicb.2020.01475 · Cited by 51 · see citing works

Untargeted and Targeted Metabolomic Profiling of Australian Indigenous Fruits

Lim, V., Gorji, S. G., Daygon, V. D., & Fitzgerald, M. A. (2020) · Metabolites · doi:10.3390/metabo10030114 · Cited by 50 · see citing works

NMR-TS: de novo molecule identification from NMR spectra

Zhang, J., Terayama, K., Sumita, M., Yoshizoe, K., Ito, K., Kikuchi, J., & Tsuda, K. (2020) · Science and Technology of Advanced Materials · doi:10.1080/14686996.2020.1793382 · Cited by 50 · see citing works

A new era in plant functional genomics

Rai, A., Yamazaki, M., & Saito, K. (2019) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2019.03.005 · Cited by 48 · see citing works

Gas chromatography/mass spectrometry-based metabolite profiling of coffee beans obtained from different altitudes and origins with various postharvest processing

Amalia, F., Aditiawati, P., Yusianto, Putri, S. P., & Fukusaki, E. (2021) · Metabolomics · doi:10.1007/s11306-021-01817-z · Cited by 49 · see citing works

Food Lipidomics for 155 Agricultural Plant Products

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Mass Spectrometry Data Repository Enhances Novel Metabolite Discoveries with Advances in Computational Metabolomics

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