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 |
| AraCyc | Mueller L. A., Zhang P., Rhee S. Y., AraCyc: A biochemical pathway database for Arabidopsis. Plant Physiology, 2003, 132, 453-460. Abstract |
| ArthropodaCyc | Baa-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 |
| AtIPD | Vranová 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 BeoCyc | Provider: BioEnergy Science Center |
| BiGG | King 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 |
| BinBase | Skogerson K., Wohlgemuth G., Barupal D. K., Fiehn O. The volatile compound BinBase mass spectral database. BMC Bioinformatics, 2011, 12, Article No 321. Abstract |
| BinDiscover | Bremer P. L., Wohlgemuth G., Fiehn O., The BinDiscover database: a biology‑focused meta‑analysis tool for 156,000 GC–TOF MS metabolome samples. Journal of Cheminformatics, 2023, 15, 66. Abstract |
| BioCyc | Caspi 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 |
| BioM2MetDisease | Xu 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 |
| Biomarker | Hossain 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 |
| BioMeta | Ott M. A., Vriend G., Correcting ligands, metabolites, and pathways. BMC Bioinformatics, 2006, 7, Article No 517. Abstract |
| BioNemo | Carbajosa G., Trigo A., Valencia A., Cases I., Bionemo: Molecular information on biodegradation metabolism. Nucleic Acids Research, 2009, 37, D598–D602. Abstract |
| BMDB | Foroutan 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 Metabolome | Saleem 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 |
| BRENDA | Chang 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 |
| BsubCyc | Caspi 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 |
| CathaCyc | Van 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 |
| CFam | Zhang 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 |
| CMBD | Chen J., Liu X., Shen L., Lin Y., Shen B., CMBD: a manually curated cancer metabolic biomarker knowledge database. Database, 2021, Article No baaa094. Abstract |
| COLMAR | Bingol 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 |
| ConsensusPathDB | Kamburov A., Stelzl U., Lehrach H., Herwig R., The ConsensusPathDB interaction database: 2013 update. Nucleic Acids Research, 2013, 41, D793-D800. Abstract |
| CornCyc | Andorf 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 Metabolome | Wishart 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 |
| Datanator | Roth 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 |
| DCABM-TCM | Liu X., Liu J., Fu B., Chen R., Jiang J., Chen H., Li R., Xing L., Yuan L., Chen X., Zhang J., Li H., Guo S., Guo F., Guo J., Liu Y., Qi Y., Yu B., Xu F., Li D., Liu Z., DCABM-TCM: A database of constituents absorbed into the blood and metabolites of traditional Chinese medicine. Journal of Chemical Information and Modeling, 2023, 63, 4948–4959. Abstract |
| DDBJ | Ara T., Kodama Y., Tokimatsu T., Fukuda F., Kosuge T., Mashima J., Tanizawa Y., Tanjo T., Ogasawara O., Fujisawa T., Nakamura Y., Arita M., DDBJ update in 2023: the MetaboBank for metabolomics data and associated metadata. Nucleic Acids Research, 2024, 52, D67–D71. Abstract |
| DEOP | Bougouffa S., Radovanovic A., Essack M., Bajic V. B., DEOP: a database on osmoprotectants and associated pathways. Database, 2014, Article No bau100. Abstract |
| Drug-Path | Zeng H., Qiu C., Cui Q., Drug-Path: a database for drug-induced pathways. Database, 2015, Article No bav061. Abstract |
| ECMDB | Sajed 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 |
| EcoCyc | Keseler 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 |
| enviPath | Wicker 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 | |
| FiehnLib | Kind 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 |
| Food Metabolome Repository | Sakurai N., Yamazaki S., Suda K., Hosoki A., Akimoto N., Takahashi H., Shibata D., Aoki Y., The Thing Metabolome Repository family (XMRs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites. Nucleic Acids Research, 2023, 51, D660–D677. Abstract |
| GDR Cyc Pathways Database | |
| Gramene | Tello-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 |
| HBDB | Kuo 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 |
| HFMDB | Karu 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 |
| HIM | Kang 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 |
| hiPathDB | Yu 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 |
| HMDB | Wishart 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 Database | Bingol 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 |
| HumanCyc | Romero 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 Atlas | Pornputtapong N., Nookaew I., Nielsen J., Human metabolic atlas: an online resource for human metabolism. Database, 2015, Article No bav068. Abstract |
| INTEDE | Zhang Y., Liu X., Li F., Yin J., Yang H., Li X., Liu X., Chai X., Niu T., Zeng S., Jia Q., Zhu F., INTEDE 2.0: the metabolic roadmap of drugs. Nucleic Acids Research, 2024, 52, D1355–D1364. Abstract |
| isoMETLIN | Cho 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 pathway | Kanehisa M., Furumichi M., Sato Y., Kawashima M., Ishiguro-Watanabe M., KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Research, 2023, 51, D587–D592. Abstract |
| KOMICS | Sakurai 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 |
| kpath | Navas-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 Pathways | Authors: Yoav Bauman, Roy Granit, Alon Vitenshtein |
| LabWorm Metabolites and Metabolomics | Authors: Yoav Bauman, Roy Granit, Alon Vitenshtein |
| MACC | Gao J., Mo S., Wang J., Zhang M., Shi Y., Zhu C., Shang Y., Tang X., Zhang S., Wu X., Xu X., Wang Y., Li Z., Zheng G., Chen Z., Wang Q., Tang K., Cao Z., MACC: a visual interactive knowledgebase of metabolite-associated cell communications. Nucleic Acids Research, 2024, 52, D633–D639. Abstract |
| MaizeCyc | Monaco 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 |
| MarkerDB | Wishart 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 |
| MedicCyc | Urbanczyk-Wochniak E., Sumner L. W., MedicCyc: a biochemical pathway database for Medicago truncatula. Bioinformatics, 2007, 23, 1418-1423. Abstract |
| MeKO | Sakurai 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 |
| MENDA | Pu 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 |
| metabolicMine | Lyne 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 |
| MetaboLights | Yurekten O., Payne T., Tejera N., Amaladoss F. X., Martin C., Williams M., O’Donovan C., MetaboLights: open data repository for metabolomics. Nucleic Acids Research, 2024, 52, D640–D646. Abstract |
| Metabolomics Workbench | Sud 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 |
| Metabolonote | Ara 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 |
| MetaCrop | Schreiber 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 |
| MetaCyc | Caspi 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 |
| MetaNetX | Moretti 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 |
| MetExplore | Cottret 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 |
| MetRxn | Kumar 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 |
| METscout | Geffers 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 |
| MiMeDB | Wishart D. S., Oler E., Peters H., Guo A., Girod S., Han S., Saha S., Lui V. W., LeVatte M., Gautam V., Kaddurah-Daouk R., Karu N., MiMeDB: the Human Microbial Metabolome Database. Nucleic Acids Research, 2023, 51, D611–D620. Abstract |
| MINE | Jeffryes 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 |
| MMCD | Cui 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 |
| MMHub | Li D., Ma B., Xu X., Chen G., Li T., He N., MMHub, a database for the mulberry metabolome. Database, 2020, Article No baaa011. Abstract |
| MMMDB | Sugimoto 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 |
| ModelSEED | Seaver 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 |
| MODEM | Liu 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 |
| MouseCyc | Evsikov 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 |
| MPMR | Syrkin 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 |
| mVOC | Lemfack M. C., Nickel J., Dunkel M., Preissner R., Piechulla B., mVOC: a database of microbial volatiles. Nucleic Acids Research, 2014, 42, D744-D748. Abstract |
| mzCloud | Broeckling 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 |
| PAMDB | Huang 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 |
| PathBank | Wishart D. S., Kruger R., Sivakumaran A., Harford K., Sanford S., Doshi R., Kehrtarpal N., Fatokun O., Doucet D., Zubkowski A., Jackson H., Sykes G., Ramirez-Gaona M., Marcu A., Li C., Yee K., Garros C., Rayat D. Y., Coleongco J., Nandyala T., Gautam V., Oler E., PathBank 2.0—the pathw a y database for model organism metabolomics. Nucleic Acids Research, 2024, 52, D654–D662. Abstract |
| PathCards | Belinky 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-MAW | Cicek 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 |
| pathDIP | Pastrello C., Kotlyar M., Abovsky M., Lu R., Jurisica I., PathDIP 5: improving coverage and making enrichment analysis more biologically meaningful. Nucleic Acids Research, 2024, 52, D663–D671. Abstract |
| PathGuide | Bader G. D., Cary M. P., Sander C., Pathguide: a pathway resource list. Nucleic Acids Research, 2006, 34, D504-D506. Abstract |
| Pathway Commons | Rodchenkov 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 |
| PCD | Provider: National University of Singapore |
| PCOSKB | Joseph 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 |
| PhytoHub | Provider: Institut National de la Recherche Agronomique |
| PID | Schaefer 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 |
| PlantCyc | Zhang 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 |
| Plant Metabolome Repository | Sakurai N., Yamazaki S., Suda K., Hosoki A., Akimoto N., Takahashi H., Shibata D., Aoki Y., The Thing Metabolome Repository family (XMRs): comparable untargeted metabolome databases for analyzing sample-specific unknown metabolites. Nucleic Acids Research, 2023, 51, D660–D677. Abstract |
| PlantMetabolomics | Bais 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 Reactome | Gupta P., Elser J., Hooks E., D’Eustachio P., Jaiswal P., Naithani S., Plant Reactome Knowledgebase: empowering plant pathway exploration and OMICS data analysis. Nucleic Acids Research, 2024, 52, D1538–D1547. Abstract |
| PMhub | Tian Z., Hu Z., Xu Y., Liu M., Liu M., Li D., Hu L., Wei G., Chen W., PMhub 1.0: a comprehensive plant metabolome database. Nucleic Acids Research, 2024, 52, D1579–D1587. Abstract |
| PMI-DB | Zhao 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 |
| PRIMe | Sakurai 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 |
| ProCyc | Dhanasekaran 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 |
| RaMP-DB | Braisted J., Patt A., Tindall C., Sheils T., Neyra J., Spencer K., Eicher T., Mathe E. A., RaMP-DB 2.0: a renovated knowledgebase for deriving biological and chemical insight from metabolites, proteins, and genes. Bioinformatics, 2023, 39, Article No btac726. Abstract |
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| VMH | Noronha 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 |
| WikiPathways | Agrawal A., Balcı H., Hanspers K., Coort S. L., Martens M., Slenter D. N., Ehrhart F., Digles D., Waagmeester A., Wassink I., Abbassi-Daloii T., Lopes E. N., Iyer A., Millán Acosta J., Willighagen L. G., Nishida K., Riutta A., Basaric H., Evelo C. T., Willighagen E. L., Kutmon M., Pico A. R., WikiPathways 2024: next generation pathway database. Nucleic Acids Research, 2024, 52, D679–D689. Abstract |
| YMDB | Ramirez-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 |
Last Updated on 27-06-2024 by Piotr Minkiewicz