| MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis J Chong, O Soufan, C Li, I Caraus, S Li, G Bourque, DS Wishart, J Xia Nucleic acids research 46 (W1), W486-W494, 2018 | 3561 | 2018 |
| MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights Z Pang, J Chong, G Zhou, DA de Lima Morais, L Chang, M Barrette, ... Nucleic acids research 49 (W1), W388-W396, 2021 | 2918 | 2021 |
| Using MetaboAnalyst 4.0 for comprehensive and integrative metabolomics data analysis J Chong, DS Wishart, J Xia Current protocols in bioinformatics 68 (1), e86, 2019 | 2065 | 2019 |
| MicrobiomeAnalyst: a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data A Dhariwal, J Chong, S Habib, IL King, LB Agellon, J Xia Nucleic acids research 45 (W1), W180-W188, 2017 | 1617 | 2017 |
| Using MicrobiomeAnalyst for comprehensive statistical, functional, and meta-analysis of microbiome data J Chong, P Liu, G Zhou, J Xia Nature protocols 15 (3), 799-821, 2020 | 1300 | 2020 |
| MetaboAnalystR: an R package for flexible and reproducible analysis of metabolomics data J Chong, J Xia Bioinformatics 34 (24), 4313-4314, 2018 | 623 | 2018 |
| MetaboAnalystR 3.0: toward an optimized workflow for global metabolomics Z Pang, J Chong, S Li, J Xia Metabolites 10 (5), 186, 2020 | 448 | 2020 |
| MetaboAnalystR 2.0: from raw spectra to biological insights J Chong, M Yamamoto, J Xia Metabolites 9 (3), 57, 2019 | 304 | 2019 |
| Using MetaboAnalyst 4.0 for metabolomics data analysis, interpretation, and integration with other omics data J Chong, J Xia Computational methods and data analysis for metabolomics, 337-360, 2020 | 164 | 2020 |
| Comprehensive meta-analysis of COVID-19 global metabolomics datasets Z Pang, G Zhou, J Chong, J Xia Metabolites 11 (1), 44, 2021 | 96 | 2021 |
| Computational approaches for integrative analysis of the metabolome and microbiome J Chong, J Xia Metabolites 7 (4), 62, 2017 | 88 | 2017 |
| Metabolomics investigation of dietary effects on flesh quality in grass carp (Ctenopharyngodon idellus) H Zhao, J Chong, R Tang, L Li, J Xia, D Li GigaScience 7 (10), giy111, 2018 | 34 | 2018 |
| Correlations between the Composition of the Bovine Microbiota and Vitamin B12 Abundance J Franco-Lopez, M Duplessis, A Bui, C Reymond, W Poisson, L Blais, ... Msystems 5 (2), 10.1128/msystems. 00107-20, 2020 | 31 | 2020 |
| Heteroresistant vancomycin intermediate coagulase negative Staphylococcus in the NICU: a systematic review J Chong, C Caya, S Lévesque, C Quach PLoS One 11 (10), e0164136, 2016 | 24 | 2016 |
| Molecular markers from different genomic compartments reveal cryptic diversity within glaucophyte species J Chong, C Jackson, J Im Kim, HS Yoon, A Reyes-Prieto Molecular phylogenetics and evolution 76, 181-188, 2014 | 22 | 2014 |
| Molecular epidemiology of a vancomycin-intermediate heteroresistant Staphylococcus epidermidis outbreak in a neonatal intensive care unit J Chong, C Quach, AC Blanchard, PG Poliquin, GR Golding, C Laferrière, ... Antimicrobial agents and chemotherapy 60 (10), 5673-5681, 2016 | 21 | 2016 |
| TrpNet: understanding tryptophan metabolism across gut microbiome Y Lu, J Chong, S Shen, JB Chammas, L Chalifour, J Xia Metabolites 12 (1), 10, 2021 | 20 | 2021 |
| Identifying glycan consumers in human gut microbiota samples using metabolic labeling coupled with fluorescence-activated cell sorting L Dridi, F Altamura, E Gonzalez, O Lui, R Kubinski, R Pidgeon, ... Nature Communications 14 (1), 662, 2023 | 8 | 2023 |
| Integrated multiple-omics reveals the regulatory mechanism underlying the effects of artificial feed and grass feeding on growth and muscle quality of grass carp … H Zhao, J Chong, D Li, J Xia Aquaculture 562, 738808, 2023 | 3 | 2023 |
| A Metabolomic Modelling Approach for Functional Microbiome Analysis J Chong McGill University (Canada), 2022 | | 2022 |
