Metabolites and metabolic pathways

AOP
AOP-Wiki
Mortensen H. M., Senn J., Levey T., Langley P., Williams A. J., The 2021 update of the EPA’s adverse outcome pathway database. Scientific Data, 2021, 8, Article No 169. Abstract
AraCycMueller L. A., Zhang P., Rhee S. Y., AraCyc: A biochemical pathway database for Arabidopsis. Plant Physiology, 2003, 132, 453-460. Abstract
ArthropodaCycBaa-Puyoulet P., Parisot N., Febvay G., Huerta-Cepas J., Vellozo A. F., Gabaldón T., Calevro F., Charles H., Colella S., ArthropodaCyc: a CycADS powered collection of BioCyc databases to analyse and compare metabolism of arthropods. Database, 2016, Article No baw081. Abstract
AtIPDVranová E., Hirsch-Hoffmann M., Gruissem W., AtIPD: A curated database of Arabidopsis isoprenoid pathway models and genes for isoprenoid network analysis. Plant Physiology, 2011, 156, 1655–1660. Abstract
BESC BeoCycProvider: BioEnergy Science Center
BiGGKing Z. A., Lu J., Dräger A., Miller P., Federowicz S., Lerman J. A., Ebrahim A., Palsson B. O., Lewis N. E., BiGG Models: A platform for integrating, standardizing and sharing genome-scale models. Nucleic Acids Research, 2016, 44, D515–D522. Abstract
BinBaseSkogerson K., Wohlgemuth G., Barupal D. K., Fiehn O. The volatile compound BinBase mass spectral database. BMC Bioinformatics, 2011, 12, Article No 321. Abstract
BioCycCaspi R., Billington R., Ferrer L., Foerster H., Fulcher C. A., Keseler I. M., Kothari A., Krummenacker M., Latendresse M., Mueller L. A., Ong Q., Paley S., Subhraveti P., Weaver D. S., Karp P. D., The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Research, 2016, 44, D471–D480. Abstract
BioM2MetDiseaseXu Y., Yang H., Wu T., Dong Q., Sun Z., Shang D., Li F., Xu Y., Su F., Liu S., Zhang Y., Li X., BioM2MetDisease: a manually curated database for associations between microRNAs, metabolites, small molecules and metabolic diseases. Database, 2017, Article No bax037. Abstract
BiomarkerHossain S. F., Huang M., Ono N., Morita A., Kanaya S., Altaf-Ul-Amin M., Development of a biomarker database toward performing disease classification and finding disease interrelations. Database, 2021, Article No baab011. Abstract
BioMetaOtt M. A., Vriend G., Correcting ligands, metabolites, and pathways. BMC Bioinformatics, 2006, 7, Article No 517. Abstract
BioNemoCarbajosa G., Trigo A., Valencia A., Cases I., Bionemo: Molecular information on biodegradation metabolism. Nucleic Acids Research, 2009, 37, D598–D602. Abstract
BMDBForoutan A., Fitzsimmons C., Mandal R., Piri-Moghadam H., Zheng J., Guo A., Li C., Guan L. L., Wishart D. S., The bovine metabolome. Metabolites, 2020, 10, Article No 233. Abstract
Bovine Rumen MetabolomeSaleem F., Bouatra S., Guo A. C., Psychogios N., Mandal R., Dunn S. M., Ametaj B. N., Wishart D. S., The bovine ruminal fluid metabolome. Metabolomics., 2013, 9, 360-378. Abstract
BRENDAChang A., Jeske L., Ulbrich S., Hofmann J., Koblitz J., Schomburg I., Neumann-Schaal M., Jahn D., Schomburg D., BRENDA, the ELIXIR core data resource in 2021: new developments and updates. Nucleic Acids Research, 2021, 49, D498–D508. Abstract
BsubCycCaspi R., Altman T., Billington R., Dreher K., Foerster H., Fulcher C. A., Holland T. A., Keseler I. M., Kothari A., Kubo A., Krummenacker M., Latendresse M., Mueller L. A., Ong Q., Paley S., Subhraveti P., Weaver D. S., Weerasinghe D., Zhang P., Karp P. D., The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases. Nucleic Acids Research, 2014, 42, D459–D471. Abstract
CathaCycVan Moerkercke A., Fabris M., Pollier J., Baart G. J. E., Rombauts S., Hasnain G., Rischer H., Memelink J., Oksman-Caldentey K.-M., Goossens A., CathaCyc, a metabolic pathway database built from Catharanthus roseus RNA-seq data. Plant and Cell Physiology, 2013, 54, 673–685. Abstract
CFamZhang C., Tao L., Qin C., Zhang P., Chen S., Zeng X., Xu F., Chen Z., Yang S. Y., Chen Y. Z., CFam: a chemical families database based on iterative selection of functional seeds and seed-directed compound clustering. Nucleic Acids Research, 2015, 43, D558–D565. Abstract
CMBDChen J., Liu X., Shen L., Lin Y., Shen B., CMBD: a manually curated cancer metabolic biomarker knowledge database. Database, 2021, Article No baaa094. Abstract
COLMARBingol K., Li D. W., Bruschweiler-Li L., Cabrera O. A., Megraw T., Zhang F., Brüschweiler R., 2015, Unified and isomer-specific NMR metabolomics database for the accurate analysis of 13C–1H HSQC spectra. ACS Chemical Biology, 2015, 10, 452–459. Abstract
ConsensusPathDBKamburov A., Stelzl U., Lehrach H., Herwig R., The ConsensusPathDB interaction database: 2013 update. Nucleic Acids Research, 2013, 41, D793-D800. Abstract
CornCycAndorf C. M., Cannon E. K., Portwood J. L., Gardiner J. M., Harper L. C., Schaeffer M. L., Braun B. L., Campbell D. A., Vinnakota A. G., Sribalusu V. V., Huerta M., Cho K. T., Wimalanathan K., Richter. J. D., Mauch E. D., Rao B. S., Birkett S. M., Richter J. D., Sen T. Z., Lawrence C. J., MaizeGDB 2015: New tools, data, and interface for the maize model organism database. Nucleic Acids Research, 2016, 44, D1195–D1201. Abstract
CSF MetabolomeWishart D. S., Lewis M. J., Morrissey J. A., Flegel M. D., Jeroncic K., Xiong Y., Cheng D., Eisner R., Gautam B., Tzur D., Sawhney S., Bamforth F., Greiner R., Li L., The human cerebrospinal fluid metabolome. Journal of Chromatography B, 2008, 871, 164–173. Abstract
DatanatorRoth Y. D., Lian Z., Pochiraju S., Shaikh B., Karr J. R., Datanator: an integrated database of molecular data for quantitatively modeling cellular behavior. Nucleic Acids Research, 2021, 49, D516–D522. Abstract
DEOPBougouffa S., Radovanovic A., Essack M., Bajic V. B., DEOP: a database on osmoprotectants and associated pathways. Database, 2014, Article No bau100. Abstract
Drug-PathZeng H., Qiu C., Cui Q., Drug-Path: a database for drug-induced pathways. Database, 2015, Article No bav061. Abstract
ECMDBSajed T., Marcu A., Ramirez M., Pon A., Guo A. C., Knox C., Wilson M., Grant J. R., Djoumbou Y., Wishart D. S., ECMDB 2.0: A richer resource for understanding the biochemistry of E. coli. Nucleic Acids Research, 2016, 44, D495–D501. Abstract
EcoCycKeseler I. M., Mackie A., Santos-Zavaleta A., Billington R., Bonavides-Martínez C., Caspi R., Fulcher C., Gama-Castro S., Kothari A., Krummenacker M., Latendresse M., Muñiz-Rascado L., Ong Q., Paley S., Peralta-Gil M., Subhraveti P., Velázquez-Ramírez D. A., Weaver D., Collado-Vides J., Paulsen I., Karp P. D., The EcoCyc database: reflecting new knowledge about Escherichia coli K-12. Nucleic Acids Research, 2017, 45, D543–D550. Abstract
enviPathWicker J., Lorsbach T., Gütlein M., Schmid E., Latino D., Kramer S., Fenner K., enviPath – The environmental contaminant biotransformation pathway resource. Nucleic Acids Research, 2016, 44, D502–D508. Abstract
ExPASy-Roche 
FiehnLibKind T., Wohlgemuth G., Lee D. Y., Lu Y., Palazoglu M., Shahbaz S., Fiehn O., FiehnLib: mass spectral and retention index libraries for metabolomics based on quadrupole and time-of-flight gas chromatography/mass spectrometry. Analytical Chemistry, 2009, 81, 10038–10048. Abstract
FOBI
FOBI visualization tool
Castellano-Escuder P., González-Domínguez R., Wishart D. S., Andrés-Lacueva C., Sánchez-Pla A., FOBI: an ontology to represent food intake data and associate it with metabolomic data. Database, 2020, Article No baaa033. Abstract
GDR Cyc Pathways Database 
GrameneTello-Ruiz M. K., Naithani S., Gupta P., Olson A., Wei S., Preece J., Jiao Y., Wang B., Chougule K., Garg P., Elser J., Kumari S., Kumar V., Contreras-Moreira B., Naamati G., George N., Cook J., Bolser D., D’Eustachio P., Stein L. D., Gupta A., Xu W., Regala J., Papatheodorou I., Kersey P. J., Flicek P., Taylor C., Jaiswal P., Ware D., Gramene 2021: harnessing the power of comparative genomics and pathways for plant research. Nucleic Acids Research, 2021, 49, D1452–D1463. Abstract
HBDBKuo T.-C., Tan C.-E., Wang S.-Y., Lin O. A., Su B.-H., Hsu M.-T., Lin J., Cheng Y.-Y., Chen C.-S., Yang Y.-C., Chen K.-H., Lin S.-W., Ho C.-C., Kuo C.-H., Tseng Y. J., Human Breathomics Database. Database, 2020, Article No baz139. Abstract
HFMDBKaru N., Deng L., Slae M., Guo A. C., Sajed T., Huynh H., Wine E., Wishart D. S., A Review on Human Fecal Metabolomics: methods, applications and the Human Fecal Metabolome Database. Analytica Chimica Acta, 2018, 1030, 1-24. Abstract
HIMKang H., Tang K., Liu Q., Sun Y., Huang Q., Zhu R., Gao J., Zhang D., Huang C., Cao Z., 2013, HIM-herbal ingredients in-vivo metabolism database. Journal of Cheminformatics, 2013, 5, Article No 28. Abstract
hiPathDBYu N., Seo J., Rho K., Jang Y., Park J., Kim W. K., Lee S., hiPathDB: a human-integrated pathway database with facile visualization. Nucleic Acids Research, 2012, 40, D797–D802. Abstract
HMDBWishart D. S., Guo A., Oler E., Wang F., Anjum A., Peters H., Dizon R., Sayeeda Z., Tian S., Lee B. L., Berjanskii M., Mah R., Yamamoto M., Jovel J., Torres-Calzada C., Hiebert-Giesbrecht M., Lui V. W., Varshavi D., Varshavi D., Allen D., Arndt D., Khetarpal N., Sivakumaran A., Harford K., Sanford S., Yee K., Cao X., Budinski Z., Liigand J., Zhang L., Zheng J., Mandal R., Karu N., Dambrova M., Schiöth H. B., Greiner R., Gautam V., HMDB 5.0: the Human Metabolome Database for 2022. Nucleic Acids Research, 2022, 50, D622–D631. Abstract
HSQC Metabolomics DatabaseBingol K., Li D.-W., Brüschweiler-Li L., Cabrera O. A., Megraw T., Zhang F., Brüschweiler R., Unified and isomer-specific NMR metabolomics database for the accurate analysis of 13C–1H HSQC Spectra. ACS Chemical Biology, 2015, 10, 452–459. Abstract
HumanCycRomero P., Wagg J., Green M. L., Kaiser D., Krummenacker M., Karp P. D., Computational prediction of human metabolic pathways from the complete human genome. Genome Biology, 2004, 6, Article No R2. Abstract
Human Metabolic AtlasPornputtapong N., Nookaew I., Nielsen J., Human metabolic atlas: an online resource for human metabolism. Database, 2015, Article No bav068. Abstract
isoMETLINCho K., Mahieu N., Ivanisevic J., Uritboonthai W., Chen Y.-J., Siuzdak G., Patti G. J., isoMETLIN: A database for isotope-based metabolomics. Analytical Chemistry, 2014, 86, 9358–9361. Abstract
KEGG pathwayKanehisa M., Furumichi M., Sato Y., Ishiguro-Watanabe M., Tanabe M., KEGG: integrating viruses and cellular organisms. Nucleic Acids Research, 2021, 49, D545–D551. Abstract
KOMICSSakurai N., Ara T., Enomoto M., Motegi T., Morishita Y., Kurabayashi A., Iijima Y., Ogata Y., Nakajima D., Suzuki H., Shibata D., Tools and databases of the KOMICS web portal for preprocessing, mining, and dissemination of metabolomics data. BioMed Research International, 2014, Article No 194812. Abstract
kpathNavas-Delgado I., García-Godoy M.-J., López-Camacho E., Rybinski M., Reyes-Palomares A., Medina M. A., Aldana-Montes J. F., kpath: integration of metabolic pathway linked data. Database, 2015, Article No bav053. Abstract
LabWorm Interaction, Network and PathwaysAuthors: Yoav BaumanRoy GranitAlon Vitenshtein
LabWorm Metabolites and MetabolomicsAuthors: Yoav BaumanRoy GranitAlon Vitenshtein
MaizeCycMonaco M. K., Sen T. Z., Dharmawardhana P. D., Ren L., Schaeffer M., Naithani S., Amarasinghe V., Thomason J., Harper L., Gardiner J., Cannon E. K. S., Lawrence C. J., Ware D., Jaiswal P., Maize metabolic network construction and transcriptome analysis. The Plant Genome, 2013, 6, doi: 10.3835/plantgenome2012.09.0025. Abstract
MarkerDBWishart D. S., Bartok B., Oler E., Liang K. Y. H., Budinski Z., Berjanskii M., Guo A., Cao X., Wilson M., MarkerDB: an online database of molecular biomarkers. Nucleic Acids Research, 2021, 49, D1259–D1267. Abstract
MedicCycUrbanczyk-Wochniak E., Sumner L. W., MedicCyc: a biochemical pathway database for Medicago truncatula. Bioinformatics, 2007, 23, 1418-1423. Abstract
MeKOSakurai T., Yamada Y., Sawada Y., Matsuda F., Akiyama K., Shinozaki K., Hirai M.Y., Saito K., PRIMe Update: innovative content for plant metabolomics and integration of gene expression and metabolite accumulation. Plant & Cell Physiology, 2013, 54, Article No e5. Abstract
MENDAPu J., Yu Y., Liu Y., Tian L., Gui S., Zhong X., Fan C., Xu S., Song X., Liu L., Yang L., Zheng P., Chen J., Cheng K., Zhou C., Wang H., Xie P., MENDA: a comprehensive curated resource of metabolic characterization in depression. Briefings in Bioinformatics, 2020, 21, 1455-1464. Abstract
metabolicMineLyne M., Smith R. N., Lyne R., Aleksic J., Hu F., Kalderimis A., Stepan R., Micklem G., MetabolicMine: an integrated genomics, genetics and proteomics data warehouse for common metabolic disease research. Database, 2013, Article No bat060. Abstract
MetaboLightsHaug K., Cochrane K., Nainala V. C., Williams M., Chang J., Jayaseelan K. V., O’Donovan C., MetaboLights: a resource evolving in response to the needs of its scientific community. Nucleic Acids Research, 2020, 48, D440–D444. Abstract
Metabolomics WorkbenchSud M., Fahy E., Cotter D., Azam K., Vadivelu I., Burant C., Edison A., Fiehn O., Higashi R., Nair K. S., Sumner S., Subramaniam S., Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools. Nucleic Acids Research, 2016, 44, D463–D470. Abstract
MetabolonoteAra T., Enomoto M., Arita M., Ikeda C., Kera K., Yamada M., Nishioka T., Ikeda T., Nihei Y., Shibata D., Kanaya S., Sakurai N., Metabolonote: a wiki-based database for managing hierarchical metadata of metabolome analyses. Frontiers in Bioengineering and Biotechnology, 2015, doi: 10.3389/fbioe.2015.00038. Abstract
MetaCropSchreiber F., Colmsee C., Czauderna T., Grafahrend-Belau E., Hartmann A., Junker A., Junker B. H., Klapperstück M., Scholz U., Weise S., MetaCrop 2.0: managing and exploring information about crop plant metabolism. Nucleic Acids Research, 2012, 40, D1173–D1177. Abstract
MetaCycCaspi R., Billington R., Keseler I. M., Kothari A., Krummenacker M., Midford P. E., Ong W. K., Paley S., Subhraveti P., Karp P. D., The MetaCyc database of metabolic pathways and enzymes – a 2019 update. Nucleic Acids Research, 2020, 48, D445–D453. Abstract
MetaNetXMoretti S., Tran V. D. T., Mehl F., Ibberson M., Pagni M., MetaNetX/MNXref: unified namespace for metabolites and biochemical reactions in the context of metabolic models. Nucleic Acids Research, 2021, 49, D570–D574. Abstract
MetExploreCottret L., Frainay C., Chazalviel M., Cabanettes F., Gloaguen Y., Camenen E., Merlet B., Heux S., Portais J.-C., Poupin N., Vinson F., Jourdan F., MetExplore: collaborative edition and exploration of metabolic networks. Nucleic Acids Research, 2018, 46, W495–W502. Abstract
MetRxnKumar A., Suthers P. F., Maranas C. D., MetRxn: A knowledgebase of metabolites and reactions spanning metabolic models and databases, BMC Bioinformatics, 2012, 13, Article No 6. Abstract
METscoutGeffers L., Tetzlaff B., Cui X., Yan J., Eichele G., METscout: a pathfinder exploring the landscape of metabolites, enzymes and transporters. Nucleic Acids Research, 2013, 41, D1047-D1054. Abstract
MINEJeffryes J. G., Colastani R. L., Elbadawi-Sidhu M., Kind T., Niehaus T. D., Broadbelt L. J., Hanson A. D., Fiehn O., Tyo K. E. J., Henry C. S., MINEs: open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics. Journal of Cheminformatics, 2015, 7, Article No 44. Abstract
MMCDCui Q., Lewis I. A., Hegeman A. D., Anderson M. E., Li J., Schulte C. F., Westler W. M., Eghbalnia H. R., Sussman M. R., Markley J. L., Metabolite identification via the Madison Metabolomics Consortium Database. Nature Biotechnology, 2008, 26, 162-164. Abstract
MMHubLi D., Ma B., Xu X., Chen G., Li T., He N., MMHub, a database for the mulberry metabolome. Database, 2020, Article No baaa011. Abstract
MMMDBSugimoto M., Ikeda S., Niigata K., Tomita M., Sato H., Soga T., MMMDB: Mouse Multiple Tissue Metabolome Database. Nucleic Acids Research, 2012, 40, DD809–D814. Abstract
ModelSEEDSeaver S. M. D., Liu F., Zhang Q., Jeffryes J., Faria J. P., Edirisinghe J. N., Mundy M., Chia N., Noor E., Beber M. E., Best A. A., DeJongh M., Kimbrel J. A., D’haeseleer P., McCorkle S. R., Bolton J. R., Pearson E., Canon S., EWood-Charlson E. M., Cottingham R. W., Adam P. Arkin A. P., Henry C. S., The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes. Nucleic Acids Research, 2021, 49, D575–D588. Abstract
MODEMLiu H., Wang F., Xiao Y., Tian Z., Wen W., Zhang X., Chen X., Liu N., Li W., Liu L., Liu J., Yan J., Liu J., MODEM: multi-omics data envelopment and mining in maize. Database, 2016, Article No baw117. Abstract
MouseCycEvsikov A. V., Dolan M. E., Genrich M. P., Patek E., Bult C. J., MouseCyc: a curated biochemical pathways database for the laboratory mouse. Genome Biology, 2009, 10, Article No R84. Abstract
MPMRSyrkin Wurtele E., Chappell J., Jones A. D., Celiz M. D., Ransom N., Hur M., Rizshsky L., Crispin M., Dixon P., Liu J., Widrlechner M. P., Nikolau B. J., Medicinal plants: a public resource for metabolomics and hypothesis development. Metabolites, 2012, 2, 1031-1059. Abstract
mVOCLemfack M. C., Nickel J., Dunkel M., Preissner R., Piechulla B., mVOC: a database of microbial volatiles. Nucleic Acids Research, 2014, 42, D744-D748. Abstract
mzCloudBroeckling C. D., Afsar F. A., Neumann S., Ben-Hur A., Prenni J. E., RAMClust: A novel feature clustering method enables spectral-matching-based annotation for metabolomics data. Analytical Chemistry, 2014, 86, 6812–6817. Abstract
PAMDBHuang W., Brewer L. K., Jones J. W., Nguyen A. T., Marcu A., Wishart D. S., Oglesby-Sherrouse A. G., Kane M. A., Wilks A., PAMDB: a comprehensive Pseudomonas aeruginosa metabolome database. Nucleic Acids Research., 2018, 46, D575–D580. Abstract
PathBankWishart D. S., Li C., Marcu A., Badran H., Pon A., Budinski Z., Patron J., Lipton D., Cao X., Oler E., Li K., Paccoud M., Hong C., Guo A. C., Chan C., Wei W., Ramirez-Gaona M., PathBank: a comprehensive pathway database for model organisms. Nucleic Acids Research, 2020, 48, D470–D478. Abstract
PathCardsBelinky F., Nativ N., Stelzer G., Zimmerman S., Stein T. I., Safran M., Lancet D., PathCards: multi-source consolidation of human biological pathways. Database, 2015, Article No bav006. Abstract
PathCase-MAWCicek A. E., Qi X., Cakmak A., Johnson S. R., Han X., Alshalwi S., Ozsoyoglu Z. M., Ozsoyoglu G., An online system for metabolic network analysis. Database, 2014, Article No bau091. Abstract
pathDIPRahmati S., Abovsky M., Pastrello C., Kotlyar M., Lu R., Cumbaa C. A., Rahman P., Chandran V., Jurisica I., pathDIP 4: an extended pathway annotations and enrichment analysis resource for human, model organisms and domesticated species. Nucleic Acids Research, 2020, 48, D479–D488. Abstract
PathGuideBader G. D., Cary M. P., Sander C., Pathguide: a pathway resource list. Nucleic Acids Research, 2006, 34, D504-D506. Abstract
Pathway CommonsRodchenkov I., Babur O., Luna A., Aksoy B. A., Wong J. V., Fong D., Franz M., Siper M. C., Cheung M., Wrana M., Mistry H., Mosier L., Dlin J., Wen Q., O’Callaghan C., Li W., Elder G., Smith P. I., Dallago C., Cerami E., Gross B., Dogrusoz U., Demir E., Bader G. D., Sander C., Pathway Commons 2019 Update: integration, analysis and exploration of pathway data. Nucleic Acids Research, 2020, 48, D489–D497. Abstract
PCDProvider: National University of Singapore
PCOSKBJoseph S., Barai R. S., Bhujbalrao R., Idicula-Thomas S., PCOSKB: A KnowledgeBase on genes, diseases, ontology terms and biochemical pathways associated with PolyCystic Ovary Syndrome. Nucleic Acids Research, 2016, 44, D1032–D1035. Abstract
PhytoHubProvider: Institut National de la Recherche Agronomique
PIDSchaefer C. F., Anthony K., Krupa S., Buchoff J., Day M., Hannay T., Buetow K. T., PID: the Pathway Interaction Database. Nucleic Acids Research, 2009, 37, D674-D679. Abstract
PlantCycZhang P., Dreher K., Karthikeyan A., Chi A., Pujar A., Caspi R., Karp P., Kirkup V., Latendresse M., Lee c., Mueller L. A., Muller R., Rhee S. Y., Creation of a genome-wide metabolic pathway database for Populus trichocarpa using a new approach for reconstruction and curation of metabolic pathways for plants. Plant Physiology, 2010, 153, 1479–1491. Abstract
PlantMetabolomicsBais P., Moon-Quanbeck S. M., Nikolau B. J., Dickerson J. A., Plantmetabolomics.org: mass spectrometry-based Arabidopsis metabolomics—database and tools update. Nucleic Acids Research, 2012, 40, D1216–D1220. Abstract
Plant ReactomeNaithani S., Gupta P., Preece J., D’Eustachio P., Elser J. L., Garg P., Dikeman D. A., Kiff J., Cook J., Olson A., Wei S., Tello-Ruiz M. K., Mundo A. F., Munoz-Pomer A., Mohammed S., Cheng T., Bolton E., Papatheodorou I., Stein L., Ware D., Jaiswal P., Plant Reactome: a knowledgebase and resource for comparative pathway analysis. Nucleic Acids Research, 2020, 48, D1093–D1103. Abstract
PMI-DBZhao T., Liu J., Zeng X., Wang W., Li S., Zang T., Peng J., Yang Y., Prediction and collection of protein–metabolite interactions. Briefings in Bioinformatics, 2021, 22, Article No bbab014. Abstract
PRIMeSakurai T., Yamada Y., Sawada Y., Matsuda F., Akiyama K., Shinozaki K., Hirai M.Y., Saito K., PRIMe Update: innovative content for plant metabolomics and integration of gene expression and metabolite accumulation. Plant & Cell Physiology, 2013, 54, Article No e5. Abstract
ProCycDhanasekaran A., Pearson J. L., Ganesan B., Weimer B. C., Metabolome searcher: a high throughput tool for metabolite identification and metabolic pathway mapping directly from mass spectrometry and using genome restriction. BMC Bioinformatics, 2015, 16, Article No 62. Abstract
ReactomeGillespie M., Jassal B., Stephan R., Milacic M., Rothfels K., Senff-Ribeiro A., Griss J., Sevilla C., Matthews L., Gong C., Deng C., Varusai T., Ragueneau E., Haider Y., May B., Shamovsky V., Weiser J., Brunson T., Sanati N., Beckman L., Shao X., Fabregat A., Sidiropoulos K., Murillo J., Viteri G., Cook J., Shorser S., Bader G., Demir E., Sander C., Haw R., Wu G., Stein L., Hermjakob H., D’Eustachio P., The reactome pathway knowledgebase 2022. Nucleic Acids Research, 2022, 50, D687–D692. Abstract
RetroRulesDuigou T., du Lac M., Carbonell P., Faulon J.-L., RetroRules: a database of reaction rules for engineering biology. Nucleic Acids Research, 2019, 47, D1229–D1235. Abstract
Saliva MetabolomeDame Z. T., Aziat F., Mandal R., Krishnamurthy R., Bouatra S., Borzouie S., Guo A. C., Sajed T., Deng L., Lin H., Liu P., Dong E., Wishart D. S., The human saliva metabolome. Metabolomics, 2015, 11, 1864–1883. Abstract
Serum MetabolomePsychogios N, Hau D. D., Peng J., Guo A. C., Mandal R., Bouatra S., Sinelnikov I., Krishnamurthy R., Eisner R., Gautam B., Young N., Xia J., Knox C., Dong E., Huang P., Hollander Z., Pedersen T. L., Smith S. R., Bamforth F., Greiner R., McManus B., Newman J. W., Goodfriend T., Wishart D. S., The human serum metabolome. PLoS ONE, 2011, 6, Article No e16957. Abstract
SistematXCosta R. P. O., Lucena L. F., Silva L. M. A., Zocolo G. J., Herrera-Acevedo C., Scotti L., Da-Costa F. B., Ionov N., Poroikov V., Muratov E. N., Scotti M. T., The SistematX web portal of natural products: an update. Journal of Chemical Information and Modeling, 2021, 61, 2516–2522. Abstract
SMPDBJewison T., Su Y., Disfany F. M., Liang Y., Knox C., Maciejewski A., Poelzer J., Huynh J., Zhou Y., Arndt D., Djoumbou Y., Liu Y., Deng L., Guo A. C., Han B., Pon A., Wilson M., Rafatnia S., Liu P., Wishart D. S., SMPDB 2.0: Big improvements to the Small Molecule Pathway Database. Nucleic Acids Research, 2014, 42, D478–D484. Abstract
SolCycFoerster H., Bombarely A., Battey J. N. D., Sierro N., Ivanov N. V., Mueller L. A., SolCyc: a database hub at the Sol Genomics Network (SGN) for the manual curation of metabolic networks in Solanum and Nicotiana specific databases. Database, 2018, Article No bay035. Abstract
SoyKBJoshi T., Patil K., Fitzpatrick M. R., Franklin L. D., Yao Q., Cook J. R., Wang Z., Libault M., Brechenmacher L., Valliyodan B., Wu X., Cheng J., Stacey G., Nguyen H. T. Xu D., Soybean Knowledge Base (SoyKB): a web resource for soybean translational genomics. BMC Genomics, 2012, 13, Article No S15. Abstract
SphinGOMAPMerrill A. H., SphinGOMAP – A web-based biosynthetic pathway map of sphingolipids and glycosphingolipids. Glycobiology, 2005, 15, 15G. Abstract
SpinCoupleKikuchi J., Tsuboi Y., Komatsu K., Gomi M., Chikayama E., Date Y., SpinCouple: development of a web tool for analyzing metabolite mixtures via two-dimensional J-resolved NMR database. Analytical Chemistry, 2016, 88, 659–665. Abstract
TMDBYue Y., Chu G.-X., Liu X.-S., Tang X., Wang W., Liu G.-J., Yang T., Ling T.-J., Wang X.-G., Zhang Z.-Z., Xia T., Wan X.-C., Bao G.-H., TMDB: A literature-curated database for small molecular compounds found from tea. BMC Plant Biology, 2014, 14, Article No 243. Abstract
TransformerHoffmann M. F., Preissner S. C., Nickel J., Dunkel M., Preissner R., Preissner S., The Transformer database: biotransformation of xenobiotics. Nucleic Acids Research, 2014, 42, D1113–D1117. Abstract
TriForCMiettinen K., Iñigo S., Kreft L., Pollier J., De Bo C., Botzki A., Coppens F., Bak S., Goossens A., The TriForC database: a comprehensive up-to-date resource of plant triterpene biosynthesis. Nucleic Acids Research, 2018, 46, D586–D594.  Abstract
TRMPZheng C. J., Zhou H., Xie B., Han L. Y., Yap C. W., Chen Y. Z., TRMP: A Database of Therapeutically Relevant Multiple-Pathways, Bioinformatics, 2004, 20, 2236-2241. Abstract
TrypanoCycShameer S., Logan-Klumpler F. J., Vinson F., Cottret L., Merlet B., Achcar F., Boshart M., Berriman M., Breitling R., Bringaud F., Bütikofer P., Cattanach A. M., Bannerman-Chukualim B., Creek D. J., Crouch K., de Koning H. P., Denise H., Ebikeme C., Fairlamb A. H., Ferguson M. A. J., Ginger M. L., Hertz-Fowler C., Kerkhoven E. J., Mäser P., Michels P. A. M., Nayak A., Nes D. W., Nolan D. P., Olsen C., Silva-Franco F., Smith t. K., Taylor M. C., Tielens A. G. M., Urbaniak M. D., van Hellemond J. J., Vincent I. M., Wilkinson S. R., Wyllie S., Opperdoes F. R., Barrett M. P., Jourdan F., TrypanoCyc: a community-led biochemical pathways database for Trypanosoma brucei. Nucleic Acids Research, 2015, 43, D637–D644. Abstract
UMBBDGao J., Ellis L. M. B., Wackett L. P., The University of Minnesota Biocatalysis/Biodegradation Database: improving public access. Nucleic Acids Research, 2010, 38, D488–D491. Abstract
UnipathwayMorgat A., Coissac E., Coudert E., Axelsen K. B., Keller G., Bairoch A., Bridge A., Bougueleret L., Xenarios I., Viari A., UniPathway: a resource for the exploration and annotation of metabolic pathways. Nucleic Acids Research, 2012, 40, D761–D769. Abstract
Urine MetabolomeBouatra S., Aziat F., Mandal R., Guo A. C., Wilson M. R., Knox C., Bjorndahl T. C., Krishnamurthy R., Saleem F., Liu P., Dame Z. T., Poelzer J., Huynh J., Yallou F. S., Psychogios N., Dong E., Bogumil R., Roehring C., Wishart D. S., 2013, The human urine metabolome. PLoS ONE, 2013, 8, Article No e73076. Abstract
VMHNoronha A., Modamio J., Jarosz Y., Guerard E., Sompairac N., Preciat G., Daníelsdóttir A. D., Krecke M., Merten D., Haraldsdóttir H. S., Heinken A., Heirendt L., Magnúsdóttir S., Ravcheev D. A., Sahoo S., Gawron P., Friscioni L., Garcia B., Prendergast M., Puente A., Rodrigues M., Roy A., Rouquaya M., Wiltgen L., Žagare A., John E., Krueger M., Kuperstein I., Zinovyev A., Schneider R., Fleming R. M. T., Thiele I., The Virtual Metabolic Human database: integrating human and gut microbiome metabolism with nutrition and disease. Nucleic Acids Research, 2019, 47, D614–D624. Abstract
WikiPathwaysMartens M., Ammar A., Riutta A., Waagmeester A., Slenter D. N., Hanspers K., Miller R. A., Digles D., Lopes E. N., Ehrhart F., Dupuis L. J., Winckers L. A., Coort S. L., Willighagen E. L., Evelo C. T., Pico A. R., Kutmon M., WikiPathways: connecting communities. Nucleic Acids Research, 2021, 49, D613–D621. Abstract
YMDBRamirez-Gaona M., Marcu A., Pon A., Guo A. C., Sajed T., Wishart N. A., Karu N., Djoumbou Feunang Y., Arndt D., Wishart D. S., YMDB 2.0: a significantly expanded version of the yeast metabolome database. Nucleic Acids Research, 2017, 45, D440–D445. Abstract