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Citing CTD/Publications/Use

Contents

  1. CTD Use
  2. Citing CTD
  3. Publications
  4. Presentations, Posters, Etc.
  5. Users of CTD Data

Top ↑ CTD Use

Terms of CTD use are described in detail on our Legal Notices page. Commercial users should direct licensing-related questions here.

Top ↑ Citing CTD

To cite CTD in your publications:

Davis AP, Wiegers TC, Johnson RJ, Sciaky D, Wiegers J, Mattingly CJ Comparative Toxicogenomics Database (CTD): update 2023. Nucleic Acids Res. 2022 Sep 28.

To cite specific data:

Curated [chemical–gene interactions|chemical–disease|gene–disease] data were retrieved from the Comparative Toxicogenomics Database (CTD), MDI Biological Laboratory, Salisbury Cove, Maine, and NC State University, Raleigh, North Carolina. World Wide Web (URL: https://ctdbase.org/). [Month, year of data retrieval].

Top ↑ Publications (49)

  1. Davis AP, Wiegers TC, Wiegers J, Wyatt B, Johnson RJ, Sciaky D, Barkalow F, Strong M, Planchart A, Mattingly CJ
    CTD Tetramers: a new online tool that computationally links curated chemicals, genes, phenotypes, and diseases to inform molecular mechanisms for environmental health.
    Toxicol Sci. 2023 Jul 24:kfad069. PMID:37486259
  2. Davis AP, Wiegers TC, Johnson RJ, Sciaky D, Wiegers J, Mattingly CJ
    Comparative Toxicogenomics Database (CTD): update 2023.
    Nucleic Acids Res. 2022 Sep 28. PMID:36169237
  3. Grondin CJ, Davis AP, Wiegers JA, Wiegers TC, Sciaky D, Johnson RJ, Mattingly CJ
    Predicting molecular mechanisms, pathways, and health outcomes induced by Juul e-cigarette aerosol chemicals using the comparative toxicogenomics database.
    Curr Res Toxicol. PMID:34458863
  4. Pinkhasova DV, Jameson LE, Conrow KD, Simeone MP, Davis AP, Wiegers TC, Mattingly CJ, Leung MCK
    Regulatory Status of Pesticide Residues in Cannabis: Implications to Medical Use in Neurological Diseases.
    Curr Res Toxicol. Volume 2, 2021, Pages 140-148. PMID:34308371
  5. Davis AP, Wiegers TC, Wiegers J, Grondin CJ, Johnson RJ, Sciaky D, Mattingly CJ
    CTD anatomy: Analyzing chemical-induced phenotypes and exposures from an anatomical perspective, with implications for environmental health studies.
    Curr Res Toxicol. Volume 2, 2021, Pages 128-139. PMID:33768211
  6. Davis AP, Grondin CJ, Johnson RJ, Sciaky D, Wiegers J, Wiegers TC, Mattingly CJ
    The Comparative Toxicogenomics Database: update 2021.
    Nucleic Acids Res. 2020 Oct 17. PMID:33068428
  7. Davis AP, Wiegers TC, Grondin CJ, Johnson RJ, Sciaky D, Wiegers J, Mattingly CJ
    Leveraging the Comparative Toxicogenomics Database to fill in knowledge gaps for environmental health: a test case for air pollution-induced cardiovascular disease.
    Toxicol Sci. 2020 Jul 14. PMID:32663284
  8. Davis AP, Wiegers J, Wiegers TC, Mattingly CJ
    Public data sources to support systems toxicology applications.
    Curr Opin Toxicol. 2019 August 16:17-24. PMID:33604492
  9. Davis AP, Grondin CJ, Johnson RJ, Sciaky D, McMorran R, Wiegers J, Wiegers TC, Mattingly CJ
    The Comparative Toxicogenomics Database: update 2019.
    Nucleic Acids Res. 2018 Sep 24. PMID:30247620
  10. Davis AP, Wiegers TC, Wiegers J, Johnson RJ, Sciaky D, Grondin CJ, Mattingly CJ
    Chemical-induced phenotypes at CTD help inform the pre-disease state and construct adverse outcome pathways.
    Toxicol Sci. 2018 May 28. PMID:29846728
  11. Grondin CJ, Davis AP, Wiegers TC, Wiegers JA, Mattingly CJ
    Accessing an Expanded Exposure Science Module at the Comparative Toxicogenomics Database.
    Environ Health Perspect. 2018 Jan 18;126(1):014501. PMID:29351546
  12. Davis AP, Grondin CJ, Johnson RJ, Sciaky D, King BL, McMorran R, Wiegers J, Wiegers TC, Mattingly CJ.
    The Comparative Toxicogenomics Database: update 2017.
    Nucleic Acids Res. 2016 Sep 19;[Epub ahead of print] PMID:27651457
  13. Grondin CJ, Davis AP, Wiegers TC, King BL, Wiegers JA, Reif DM, Hoppin JA, Mattingly CJ.
    Advancing Exposure Science through Chemical Data Curation and Integration in the Comparative Toxicogenomics Database.
    Environ Health Perspect. 2016 May 12 PMID:27170236
  14. Davis AP, Wiegers TC, King BL, Wiegers J, Grondin CJ, Sciaky D, Johnson RJ, Mattingly CJ.
    Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.
    PLoS One. 2016 May 12;11(5):e0155530. PMID:27171405
  15. Pelletier D, Wiegers TC, Enayetallah A, Kibbey C, Gosink M, Koza-Taylor P, Mattingly CJ, Lawton M.
    ToxEvaluator: an integrated computational platform to aid the interpretation of toxicology study-related findings.
    Database (Oxford). 2016 May 9;2016. pii: baw062. PMID:27161010
  16. Li J, Sun Y, Johnson RJ, Sciaky D, Wei CH, Leaman R, Davis AP, Mattingly CJ, Wiegers TC, Lu Z.
    BioCreative V CDR task corpus: a resource for chemical disease relation extraction.
    Database (Oxford). 2016 May 9;2016. pii: baw068 PMID:27161011
  17. Wei CH, Peng Y, Leaman R, Davis AP, Mattingly CJ, Li J, Wiegers TC, Lu Z.
    Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task.
    Database (Oxford). 2016 Mar 19;2016. pii: baw032. PMID:26994911
  18. Mattingly CJ, Boyles R, Lawler CP, Haugen AC, Dearry A, Haendel M.
    Laying a Community-Based Foundation for Data-Driven Semantic Standards in Environmental Health Sciences.
    Environ Health Perspect. 2016 Feb 12. PMID:26871594
  19. Davis AP, Grondin CJ, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, King BL, Wiegers TC, Mattingly CJ.
    The Comparative Toxicogenomics Database's 10th year anniversary: update 2015.
    Nucleic Acids Res. 2015 Jan;43 (Database issue): D914-20. PMID:25326323
  20. Wiegers TC, Davis AP, Mattingly CJ.
    Web services-based text-mining demonstrates broad impacts for interoperability and process simplification.
    Database (Oxford). 2014 Jun 10:bau050. PMID:24919658
  21. Comeau DC, Batista-Navarro RT, Dai HJ, Dogan RI, Yepes AJ, Khare R, Lu Z, Marques H, Mattingly CJ, Neves M, Peng Y, Rak R, Rinaldi F, Tsai RT, Verspoor K, Wiegers TC, Wu CH, Wilbur WJ.
    BioC interoperability track overview.
    Database (Oxford). 2014 Jun 30:bau053. PMID:24980129
  22. Arighi CN, Wu CH, Cohen KB, Hirschman L, Krallinger M, Valencia A, Lu Z, Wilbur JW, Wiegers TC
    BioCreative-IV virtual issue.
    Database (Oxford). 2014 May 22:bau039. PMID:24852177
  23. Davis AP, Wiegers TC, Roberts PM, King BL, Lay JM, Lennon-Hopkins K, Sciaky D, Johnson R, Keating H, Greene N, Hernandez R, McConnell KJ, Enayetallah AE, Mattingly CJ.
    A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions.
    Database (Oxford). 2013 Nov 28:bat080. PMID:24288140
  24. Wiegers TC, Davis AP, Mattingly CJ.
    Web services-based text-mining demonstrates broad impacts for interoperability and process simplification.
    Proceedings of the Fourth BioCreative Evaluation Workshop 1: 69-84.
  25. Comeau DC, Islamaj DR, Ciccarese P, Cohen KB, Krallinger M, Leitner F, Lu Z, Peng Y, Rinaldi F, Torii M, Valencia A, Verspoor K, Wiegers TC, Wu CH, Wilbur WJ.
    BioC: a minimalist approach to interoperability for biomedical text processing.
    Database (Oxford). 2013 Sep 18:bat064. PMID:24048470
  26. Davis AP, Wiegers TC, Johnson RJ, Lay JM, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, Murphy CG, Mattingly CJ.
    Text mining effectively scores and ranks the literature for improving chemical-gene-disease curation at the Comparative Toxicogenomics Database.
    PLoS One. 2013 Apr 17;8(4):e58201. PMID:23613709
  27. Davis AP, Murphy CG, Johnson R, Lay JM, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, King BL, Rosenstein MC, Wiegers TC, Mattingly CJ.
    The Comparative Toxicogenomics Database: update 2013.
    Nucleic Acids Res. 2013 Jan 1;41(D1):D1104-14. PMID:23093600
  28. Davis AP, Johnson RJ, Lennon-Hopkins K, Sciaky D, Rosenstein MC, Wiegers TC, Mattingly CJ.
    Targeted journal curation as a method to improve data currency at the Comparative Toxicogenomics Database.
    Database (Oxford). 2012 Dec 6;2012:bas051. PMID:23221299
  29. Wiegers TC, Davis AP, Mattingly CJ.
    Collaborative biocuration--text-mining development task for document prioritization for curation.
    Database (Oxford). 2012 Nov 22;2012:bas037. PMID:23180769
  30. King BL, Davis AP, Rosenstein MC, Wiegers TC, Mattingly CJ.
    Ranking Transitive Chemical-Disease Inferences Using Local Network Topology in the Comparative Toxicogenomics Database.
    PLoS One. 2012;7(11):e46524. PMID:23144783
  31. Hirschman L, Burns GA, Krallinger M, Arighi C, Cohen KB, Valencia A, Wu CH, Chatr-Aryamontri A, Dowell KG, Huala E, Lourenço A, Nash R, Veuthey AL, Wiegers T, Winter AG.
    Text mining for the biocuration workflow.
    Database (Oxford). 2012 Apr 18;2012:bas020. PMID:22513129
  32. Bello SM, Richardson JE, Davis AP, Wiegers TC, Mattingly CJ, Dolan ME, Smith CL, Blake JA, Eppig JT.
    Disease model curation improvements at Mouse Genome Informatics.
    Database (Oxford). 2012 Mar 20;2012:bar063. PMID:22434831
  33. Davis AP, Wiegers TC, Rosenstein MC, Mattingly CJ.
    MEDIC: a practical disease vocabulary used at the Comparative Toxicogenomics Database.
    Database (Oxford). 2012 Mar 20;2012:bar065. PMID:22434833
  34. Mattingly CJ, McKone TE, Callahan MA, Blake JA, Cohen Hubal EA.
    Providing the Missing Link: the Exposure Science Ontology ExO.
    Environ Sci Technol. 2012 Mar 20;46(6):3046-53. PMID:22324457
  35. Davis AP, Rosenstein MC, Wiegers TC, Mattingly CJ.
    DiseaseComps: a metric that discovers similar diseases based upon common toxicogenomic profiles at CTD.
    Bioinformation. 2011 Oct 14;7(4):154-6. PMID:22125387
  36. Davis AP, Wiegers TC, Rosenstein MC, Murphy CG, Mattingly CJ.
    The curation paradigm and application tool used for manual curation of the scientific literature at the Comparative Toxicogenomics Database.
    Database (Oxford). 2011 Sep 20;2011:bar034. PMID:21933848
  37. Mattingly CJ.
    Understanding environment-disease connections: An introduction to the Comparative Toxicogenomics Database (CTD).
    NCI-Nature Pathway Interaction Database. doi:10.1038/pid.2011.2 (2011).
  38. Davis AP, King BL, Mockus S, Murphy CG, Saraceni-Richards C, Rosenstein M, Wiegers T, Mattingly CJ.
    The Comparative Toxicogenomics Database: update 2011.
    Nucleic Acids Res. 2011 Jan;39(Database issue):D1067-72. PMID:20864448
  39. Davis AP, Murphy CG, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Hampton TH, Mattingly CJ.
    GeneComps and ChemComps: a new CTD metric to identify genes and chemicals with shared toxicogenomic profiles.
    Bioinformation. 2009 Oct 15;4(4):173-4. PMID:20198196
  40. Wiegers TC, Davis AP, Cohen KB, Hirschman L, Mattingly CJ.
    Text mining and manual curation of chemical-gene-disease networks for the Comparative Toxicogenomics Database (CTD).
    BMC Bioinformatics. 2009 Oct 8;10(1):326. PMID:19814812
  41. Mattingly CJ, Hampton T, Brothers K, Griffin NE, Planchart AJ.
    Perturbation of defense pathways by low-dose arsenic exposure in zebrafish embryos.
    Environ Health Perspect. 2009 Jun;117(6):981-7. PMID:19590694
  42. Gohlke JM, Thomas R, Zhang Y, Rosenstein MC, Davis AP, Murphy C, Becker KG, Mattingly CJ, Portier CJ.
    Genetic and environmental pathways to complex diseases.
    BMC Syst Biol. 2009 May 5;3(1):46. PMID:19416532
  43. Mattingly CJ.
    Chemical databases for environmental health and clinical research.
    Toxicol Lett. 2009 Apr 10;186(1):62-5. PMID:18996453
  44. Davis AP, Murphy CG, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Mattingly CJ.
    Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical-gene-disease networks.
    Nucleic Acids Res. 2009 Jan;37(Database issue):D786-92. PMID:18782832
  45. Davis AP, Murphy CG, Rosenstein MC, Wiegers TC, Mattingly CJ.
    The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study.
    BMC Med Genomics. 2008 Oct 9;1(1):48. PMID:18845002
  46. Mattingly CJ, Colby GT, Rosenstein MC, Forrest JN, Boyer JL.
    The Comparative Toxicogenomics Database (CTD): a resource for comparative toxicological studies.
    J Exp Zoolog A Comp Exp Biol. 2006 Sep 1;305(9):689-92. PMID:16902965
  47. Mattingly CJ, Rosenstein MC, Davis AP, Colby GT, Forrest JN, Boyer JL.
    The Comparative Toxicogenomics Database: a cross-species resource for building chemical-gene interaction networks.
    Toxicol Sci. 2006 Aug;92(2):587-95. PMID:16675512
  48. Mattingly CJ, Colby GT, Rosenstein MC, Forrest JN, Boyer JL.
    Promoting comparative molecular studies in environmental health research: an overview of the comparative toxicogenomics database (CTD).
    Pharmacogenomics J. 2004;4(1):5-8. PMID:14735110
  49. Mattingly CJ, Colby GT, Forrest JN, Boyer JL.
    The Comparative Toxicogenomics Database (CTD).
    Environ Health Perspect. 2003 May;111(6):793-5. PMID:12760826

Top ↑ Presentations, Posters, Etc. (78)

  1. Mattingly CJ, Wyatt B, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Abrat S, Davis AP.
    Comparative Toxicogenomics Database: A tool to investigate the effects of environmental exposures on the etiology of Alzheimer’s disease.
    Sapporo Exposome. Sopporo, Japan. May 24-27, 2024.
  2. Davis AP.
    CTD Tetramers: filling environmental health knowledge gaps with computed molecular mechanisms.
    NIH/NLM/NCBI Journal Club. Virtual. May 22, 2024.
  3. Mattingly CJ.
    Comparative Toxicogenomics Database (CTD).
    NINDS, NIEHS, UDN, and External Experts Environmental Trigger Workshop. Virtual. May 6, 2024.
  4. Davis AP, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Wyatt B, Abrat S, Mattingly CJ.
    CTD’s 20th anniversary: providing curated data for environmental health, from molecules to populations.
    Society of Toxicology 63rd Annual Meeting. Salt Lake City, UT, USA. March 10-14, 2024.
  5. Wyatt B, Davis AP, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Abrat S, Mattingly CJ.
    Surveying environmental influences for Alzheimer disease using the public Comparative Toxicogenomics Database.
    Society of Toxicology 63rd Annual Meeting. Salt Lake City, UT, USA. March 10-14, 2024.
  6. Mattingly CJ, Wyatt B, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Abrat S, Davis AP
    CTD’s 20th anniversary: providing curated data for environmental health, from molecules to populations.
    DRKB Program Network Meeting. Rockville, MD, USA. February 28-29, 2024.
  7. Wyatt B, Davis AP, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Abrat S, Mattingly CJ.
    CTD integrates curated chemical, gene, phenotype, anatomy, disease, and exposure data to fill knowledge gaps for environmental health: PFAS-childhood asthma as a use case.
    USA Exposome Symposium: Children’s Health, Environmental Justice, and the Exposome. Nashville, TN, USA. January 22-24, 2024.
  8. Davis AP.
    Using CTD to fill knowledge gaps for environmental health.
    Jonathan Hamm Lab Seizure Project Meeting. Virtual. December 15, 2023.
  9. Davis AP.
    Using CTD to fill knowledge gaps for environmental neuroscience.
    NIH Environmental Neuroscience Working Group. Virtual. August 29 2023.
  10. Mattingly CJ, Wiegers TC, Wiegers JA, Sciaky D, Johnson RJ, Davis AP.
    Comparative Toxicogenomics Database: a tool to investigate the effects of environmental exposures on the etiology of Alzheimer’s disease.
    Alzheimer’s Association International Conference. Amsterdam, Netherlands. July 16-20, 2023.
  11. Mattingly CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP.
    CTD Tetramers: a new online tool to fill knowledge gaps about environmental health.
    Society of Toxicology 62nd Annual Meeting. Nashville, TN, USA. March 19-23, 2023.
  12. Davis AP.
    Introduction to CTD: navigating curated data t fill in knowledge gaps for environmental health.
    The Jackson Laboratory. Bar Harbor, ME, USA. July 12, 2022
  13. Davis AP, Grondin CJ, Wiegers JA, Wiegers TC, Sciaky D, Johnson RJ, Mattingly CJ.
    Analyzing e-cigarette aerosol chemicals using the Comparative Toxicogenomics Database.
    Society of Toxicology 61st Annual Meeting. San Diego, CA, USA. March 28-31, 2022.
  14. Davis AP, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Mattingly CJ.
    CTD: integrating chemical, gene, phenotype, anatomy, disease, and exposure data to fill in knowledge gaps for environmental health
    Society of Toxicology 61st Annual Meeting. San Diego, CA, USA. March 28-31, 2022.
  15. Jameson L, Rivera A, Conrow K, Pinkhasova D, Jourachian N, Johnson S, Davis AP, Wiegers T, Sammi S, Mattingly CJ, Afia I, Orser C, Cannon J, Leung M.
    Mechanism of neurological hazards from insecticide exposure in cannabis.
    Society of Toxicology 61st Annual Meeting. San Diego, CA, USA. March 28-31, 2022.
  16. Davis AP.
    Leveraging CTD data to fill in knowledge gaps for environmental health.
    OpenTox Euro. Virtual. September 24, 2021.
  17. Grondin C, Davis AP, Johnson R, Sciaky D, Wiegers J, Wiegers T, Mattingly CJ.
    Analyzing the Effects of Emerging Environmental Exposures on Human Health Using the Comparative Toxicogenomics Database.
    International Society of Exposure Science. Virtual. August 30-September 2, 2021.
  18. Davis AP.
    Leveraging CTD to fill in knowledge gaps for environmental health science.
    NTP Data Science Seminar Series. Virtual. June 19, 2021.
  19. Davis AP.
    Introduction to CTD.
    Arizona State University. Virtual. March 18, 2021.
  20. Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP.
    Comparative Toxicogenomics Database (CTD): linking chemicals, genes, phenotypes, diseases, and exposures to fill in knowledge gaps for environmental health.
    Society of Toxicology 60th Annual Meeting. Virtual. March 12-16, 2021.
  21. Pinkhasova S, Jameson L, Conrow K, Simeone M, Davis AP, Wiegers T, Mattingly CJ, Leung M.
    Regulatory status of pesticide residues I cannabis: implications to medical use in neurological diseases.
    Society of Toxicology 60th Annual Meeting. Virtual. March 12-16, 2021.
  22. Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP.
    The Comparative Toxicogenomics Database (CTD): a comprehensive view of chemical exposures, mechanisms, and biological effects.
    Society of Toxicology 59th Annual Meeting. Virtual. March 15-19, 2020.
  23. Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP.
    The Comparative Toxicogenomics Database (CTD): mechanism meets exposure science illustrated through a bisphenol A-diabetes case study.
    Society of Toxicology 58th Annual Meeting. Baltimore, MD, USA. March 11-14, 2019.
  24. Grondin CJ, Davis AP, Wiegers JA, Wiegers TC, Johnson RJ, Sciaky D, Mattingly CJ.
    Using the Comparative Toxicogenomics Database to further our understanding of environmental exposures on human health.
    International Society of Exposure Science. Ottawa, Canada. August 27-29, 2018.
  25. Davis AP, Wiegers TC, Johnson RJ, Sciaky D, Grondin CJ, Wiegers JA, Mattingly CJ.
    Chemical-induced phenotypes at CTD: informing the pre-disease state and adverse outcome pathways.
    Society of Toxicology 57th Annual Meeting. San Antonio, TX, USA. March 11-15, 2018.
  26. Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP.
    Comparative Toxicogenomics Database (CTD): an integrated resource for chemical, gene, phenotype, and exposure data.
    Society of Toxicology 57th Annual Meeting. San Antonio, TX, USA. March 11-15, 2018.
  27. Grondin CJ, Davis AP, Wiegers JA, Wiegers TC, Green A, Planchart A, Mattingly CJ.
    Facilitating exposure data analysis in the Comparative Toxicogenomics Database: a case study of heavy metals and metabolic syndrome.
    Society of Toxicology 57th Annual Meeting. San Antonio, TX, USA. March 11-15, 2018.
  28. Davis AP, Johnson RJ, Sciaky D, Grondin CJ, Wiegers JA, Wiegers TC, Mattingly CJ.
    Chemical-phenotype curation at the Comparative Toxicogenomics Database.
    10th International Biocuration Conference. Palo Alto, CA, USA. March 26-29, 2017.
  29. Grondin CJ, Davis AP, Wiegers J, Wiegers, TC, King BL, Mattingly CJ.
    Exposure science in CTD: linking chemical stressors to outcomes via an Exposure Ontology.
    10th International Biocuration Conference. Palo Alto, CA, USA. March 26-29, 2017.
  30. Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP.
    Comparative Toxicogenomics Database (CTD): integrating chemical, gene, phenotype, disease, and exposure science data.
    Society of Toxicology 56th Annual Meeting. Baltimore, MD, USA. March 12-16, 2017.
  31. Davis AP.
    Curation and integration of exposure science at the Comparative Toxicogenomics Database: an introduction for new users.
    Emory Exposome Summer Course. Atlanta, GA, USA. June 13-15, 2016.
  32. Mattingly CJ, Grondin CJ, Johnson R, Sciaky D, King BL, Wiegers JA, Wiegers TC, Davis AP.
    The Comparative Toxicogenomics Database (CTD): Expanding Exposome and Phenotype Content to Elucidate Chemical-Disease Relationships.
    Society of Toxicology Annual Meeting. New Orleans, LA, USA. Mar 13-17, 2016.
  33. Grondin CJ, Davis AP, Wiegers TC, Wiegers JA, Mattingly CJ.
    The Comparative Toxicogenomics Database (CTD): Advancing understanding of molecular connections among chemicals, genes and diseases.
    American Chemical Society National Meeting. San Diego, CA, USA Mar 13-17, 2016.
  34. Collier G, Planchart A, Reif DM, Mattingly CJ.
    Elucidating Correlations between High-Throughput Chemical Screening and Curated Literature.
    Society of Toxicology Annual Meeting. New Orleans, LA, USA. Mar 13-17, 2016.
  35. Wiegers TC, Lu, Z.
    BioCreative V Track 3: Chemical-Disease Relation AND Disease Named Entity Recognition and Normalization.
    BioCreative V Challenge Workshop. cicCartuja, Sevilla, Spain. Sept 9-11, 2015.
  36. Grondin CJ, Davis AP, Wiegers JA, Wiegers TC, Mattingly CJ.
    Exposure Science Data and the Comparative Toxicogenomics Database.
    Society of Toxicology Annual Meeting. San Diego, CA, USA. Mar 22-26, 2015.
  37. Mattingly CJ, Grondin CJ, Lennon-Hopkins K, Saracini-Richards C, Sciaky D, Wiegers JA, McMorran R, King BL, Wiegers TC, Davis AP.
    The Comparative Toxicogenomics Database: Ten Years in the Making.
    Society of Toxicology Annual Meeting. San Diego, CA, USA. Mar 22-26, 2015.
  38. Grondin CJ, Davis AP, Mattingly CJ.
    Exposure data and the Comparative Toxicogenomics Database (CTD).
    Society of Toxicology Annual Meeting. Phoenix, AZ, USA. Mar 23-27, 2014.
  39. Davis AP, Mattingly CJ, Murphy CG, Lay JM, Lennon-Hopkins K, Sciaky D, Saracini-Richards C, King BL, Rosenstein MC, Wiegers TC.
    The Comparative Toxicogenomics Database.
    Society of Toxicology Annual Meeting. Phoenix, AZ, USA. Mar 23-27, 2014.
  40. Mattingly CJ.
    The Comparative Toxicogenomics Database (CTD): Facilitating Mechanistic Understanding of Chemical Effects.
    Society of Toxicology Annual Meeting. Phoenix, AZ, USA. Mar 23-27, 2014.
  41. Mattingly CJ.
    The Comparative Toxicogenomics Database (CTD): Leveraging Species Diversity to Understand Mechanisms of Toxicity.
    Society of Toxicology Annual Meeting. Phoenix, AZ, USA. Mar 23-27, 2014.
  42. Murphy CG, Mattingly CJ, Davis AP
    Exposure Data Curation for Integration into the Comparative Toxicogenomics Database (CTD).
    Society of Toxicology Annual Meeting. San Antonio, TX, USA. Mar 10-14, 2013.
  43. Mattingly CJ, Murphy CG, Johnson R, Lay JM, Lennon-Hopkins K, Saracini-Richards C, Sciaky D, King BL, Rosenstein MC, Wiegers TC, Davis AP.
    The Comparative Toxicogenomics Database.
    Society of Toxicology Annual Meeting. San Antonio, TX, USA. Mar 10-14, 2013.
  44. Wiegers TC
    BioCreative IV Track 3 CTD: Interoperability and Web Service-based NER
    BioCreative IV Conference. Bethesda, MD, USA. Oct 7-9, 2013.
  45. Wiegers TC
    BioC for NER Web Services-Based High Level Inter-process Communications
    BioCreative IV Conference. Bethesda, MD, USA. Oct 7-9, 2013.
  46. Wiegers TC, Davis AP, Mattingly CJ.
    Collaborative Biocuration--Text Mining Development Task for Document Prioritization for Curation.
    BioCreative Workshop 2012. Georgetown University, Washington, DC, USA. Apr 4-5, 2012.
  47. Mattingly CJ, Davis AP, Murphy CG, Saraceni Richards CA, Mockus S, Rosenstein MC, Wiegers TC, King B.
    Predicting Mechanisms of Chemical Toxicity using the Comparative Toxicogenomics Database (CTD).
    Society of Toxicology Annual Meeting. San Francisco. CA, USA. Mar 11-15, 2012.
  48. Murphy CG, Davis AP, Saracini-Richards CA, Rosenstein MC, Wiegers TC, Mattingly CJ.
    Using CTD to discover and predict molecular connections between environmental chemicals and human health.
    Society of Toxicology Annual Meeting. San Francisco. CA, USA. Mar 11-15, 2012.
  49. Bello SM, Davis AP, Wiegers TC, Dolan ME, Smith C, Richardson J, Blake J, Eppig JT, Mattingly CJ.
    Waiting for a robust Disease Ontology: a merger of OMIM and MeSH as a practical interim solution.
    International Conference on Biomedical Ontology, University at Buffalo, NY, USA. Jul 26-30, 2011.
  50. Rosenstein MC, Wiegers TC, McMorran RA.
    Oracle to PostgreSQL: CTD's Path to Database Happiness.
    Mouse Genome Informatics Group Meeting. The Jackson Laboratory. Bar Harbor, ME, USA. Jun 8, 2011.
  51. Davis AP, Murphy CG, Saraceni-Richards CA, Mockus S, Rosenstein MC, Wiegers TC, King B, Mattingly CJ.
    Environmental chemicals and human health: uncovering the connections with CTD.
    Society of Toxicology Annual Meeting. Washington, DC, USA. Mar 7-10, 2011.
  52. Davis AP, Murphy CG, Mattingly CJ.
    The Comparative Toxicogenomics Database.
    Society of Toxicology Annual Meeting. Washington, DC, USA. Mar 7-10, 2011.
  53. Davis AP.
    Using CTD to understand BPA.
    NIEHS BPA Grantee Research Update and Coordination Meeting. Research Triangle Park, NC, USA. Sep 21-22, 2010.
  54. Davis AP.
    New features at CTD.
    The OpenHelix Blog. May 18, 2010.
  55. Murphy CG.
    Use and development of ontologies in the Comparative Toxicogenomics Database (CTD).
    Protein Ontology 3rd Annual Meeting. University of Delaware, Newark, DE, USA. Apr 26-27, 2010.
  56. Davis AP, Murphy CG, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Mattingly CJ.
    CTD: exploring over 1,000,000 chemical-gene-disease interactions.
    Society of Toxicology Annual Meeting. Salt Lake City, UT, USA. Mar 7-11, 2010.
  57. Davis AP.
    Mapping OMIM to MeSH: a disease hierarchy for CTD.
    Mouse Genome Informatics Group Meeting. The Jackson Laboratory. Bar Harbor, ME, USA. Feb 23, 2010.
  58. Wiegers TC, Murphy C, Saraceni-Richards CA, Rosenstein MC, Davis AP, Mattingly CJ.
    The Comparative Toxicogenomics Database (CTD) Text Mining Study.
    3rd International Biocuration Conference. Berlin, Germany. Apr 2009.
  59. Mattingly CJ, Murphy C, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Davis AP.
    The Comparative Toxicogenomics Database (CTD): A discovery tool for identifying chemical-gene-disease networks.
    Society of Toxicology Annual Meeting. Baltimore, MD, USA. Mar 2009.
  60. Mattingly CJ, Murphy C, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Davis AP.
    Using the Comparative Toxicogenomics Database (CTD) to identify chemical-gene-disease associations.
    Society of Experimental Toxicology and Chemistry. Tampa, FL, USA. Nov 2008.
  61. Mattingly CJ.
    The Comparative Toxicogenomics Database.
    Annual environmental health sciences core centers meeting. Philadelphia, PA, USA. Oct 2008.
  62. Davis AP, Murphy CG, Rosenstein MC, Wiegers TC, Boyer JL, Mattingly CJ.
    Using CTD to discover chemical-gene-disease associations: arsenic as a case study.
    Mechanisms of Toxicity, Gordon Research Conference, Bates College, Lewiston, ME, USA. Jul 27-Aug 1, 2008.
  63. Mattingly CJ.
    Using the Comparative Toxicogenomics Database (CTD) to Explore Chemical-Gene-Disease Connections.
    University of Maine Graduate School of Biomedical Sciences Symposium. Orono, ME, USA. May 2008.
  64. Mattingly CJ.
    The Comparative Toxicogenomics Database (CTD): Promoting understanding of chemical-gene-disease associations.
    NERC International Collaboration Initiative: Bioinformatics Workshop. Birmingham, UK. Mar 2008.
  65. Mattingly CJ, Davis AP, Rosenstein MC, Wiegers T, Forrest JN, Boyer JL.
    Using the Comparative Toxicogenomics Database to identify chemical-gene-disease associations: arsenic as a case study.
    Society of Toxicology Annual Meeting. Seattle, WA, USA. Mar 2008.
  66. Davis AP, Murphy C, Rosenstein MC, Wiegers T, Forrest JN, Boyer JL, Mattingly CJ.
    Curating the Comparative Toxicogenomics Database: a knowledge and discovery environment for chemical-gene-disease associations. [Abstract]
    Second International Biocuration Meeting. San Jose, CA, USA. Oct 2007.
  67. Mattingly CJ.
    The Comparative Toxicogenomics Database: Promoting Understanding About the Mechanisms of Chemical Actions. Toxicology Division of the American Society for Pharmacology and Experimental Therapeutics (ASPET).
    "Toxicogenomics Approaches for Evaluating Drug and Chemical Toxicity" Symposium at the Experimental Biology Annual Meeting. Washington, DC, USA. Apr 2007.
  68. Davis AP, Mattingly CJ, Rosenstein MC, Wiegers T, Forrest JN, Boyer JL.
    The Comparative Toxicogenomics Database: connecting chemicals, genes, and diseases. [Abstract]
    Society of Toxicology Annual Meeting. Charlotte, NC, USA. Mar 2007.
  69. Mattingly CJ, Rosenstein MC, Davis AP, Colby GC, Forrest JN, Boyer JL.
    Comparative Toxicogenomics Database (CTD): Promoting Understanding of Chemical-Gene Interactions.
    Keystone: the Molecular and Integrative Basis for Toxic Responses. Victoria, BC. May 2006.
  70. Davis AP, Mattingly CJ, Rosenstein MC, Forrest JN, Boyer JL.
    The Comparative Toxicogenomics Database: A Public Resource for Chemical-Gene and Chemical-Protein Interactions.
    EPA Science Forum 2006, U.S Environmental Protection Agency, Washington, DC, USA. May 2006.
  71. Mattingly CJ, Rosenstein MC, Davis AP, Forrest JN, Boyer JL.
    The Comparative Toxicogenomics Database (CTD).
    Society of Toxicology Annual Meeting. San Diego, CA, USA. Mar 2006.
  72. Colby GT, Mattingly CJ, Rosenstein, MC, Forrest JN, Boyer JL.
    Data Integration in the Comparative Toxicogenomics Database (CTD).
    Annual meeting of the International Society for Computational Biology. Detroit, MI, USA. Jun 2005.
  73. Mattingly CJ.
    Cross-Species Comparative Approaches to Understanding Chemical-Gene Interactions.
    15th International Conference of Comparative Endocrinology. Boston, MA, USA. May 2005.
  74. Mattingly CJ.
    Comparative Approaches to Understanding Gene-Chemical Interactions.
    Northland Chapter of the Society of Toxicology Meeting. Minneapolis, MN, USA. Apr 2005.
  75. Mattingly CJ, Colby GT, Rosenstein MC, Forrest JN, Boyer JL.
    The Comparative Toxicogenomics Database (CTD).
    Society of Toxicology Annual Meeting. New Orleans, LA, USA. Mar 2005.
  76. Mattingly CJ.
    The Comparative Toxicogenomics Database (CTD): Comparative Molecular Approaches to Environmental Health Research.
    American Chemical Society National Meeting. Philadelphia, PA, USA. Aug 2004.
  77. Mattingly CJ.
    Comparative Approaches to Understanding Mechanisms of Toxicity: CTD.
    2004 World Congress on In Vitro Biology. San Francisco, CA, USA. May 2004.
  78. Mattingly CJ, Colby GT, Rosenstein MC, Forrest JN, Boyer JL.
    The Comparative Toxicogenomics Database (CTD).
    Society of Toxicology Annual Meeting. Salt Lake City, UT, USA. Mar 2004.

Top ↑ Users of CTD Data

  1. ABCkb: Aliment to Bodily Condition Knowledgebase, connecting plants to human health.
  2. AddictedChem: comprehensive database of controlled substances.
  3. ADRAlert: Adverse Drug Reaction Alert-gene.
  4. AGCOH: Atlas of Genetics and Cytogenetics in Oncology and Haematology.
  5. AgeAnno: Single cell annotation of aging in human.
  6. AlzBase: Alzheimer Database, an integrative database for gene dysregulation in Alzheimer disease.
  7. ANCO-GeneDB: Alcohol Nicotine Cocaine Opiate addiction-associated Gene Database.
  8. AOP-DB: Adverse Outcome Pathway Database, describes progression of a toxicity pathway from molecular perturbation to population-level outcome.
  9. AOPERA: Adverse Outcome Pathway Exploratory Research Assistant.
  10. AutismKB 2.0: Evidence-based knowledgebase of autism spectrum disorder.
  11. BIAdb: Benzylisoquinoline Alkaloids Database.
  12. BiFusion: Bipartite graph convolution network model for drug repurposing through heterogeneous information fusion.
  13. Bio2RDF: Linked data for the life sciences.
  14. BioConceptVec: Captures related concepts based on their surrounding contextual information in the literature.
  15. bioDBnet: Database to Database converstion tool, including to CTD disease information.
  16. BioGraph: Data integration and data mining platform for the exploration and discovery of biomedical information.
  17. BIOINTMED: Integrated Biomedical Knowledge Base with Ontologies and Clinical Trials.
  18. BioThings Explorer: Query engine for federated knowledge graph of biomedical APIs.
  19. BioXM: Biomax knowledge management system.
  20. Blood Exposome Database: collection of chemical compounds found in the blood that were automatically extracted by text mining the content of PubMed and PubChem databases.
  21. BPA Genomics: Genomics data portal related to health effects of bisphenol A exposure.
  22. BrainBase: Curated knowledgebase for brain diseases.
  23. C2HI: Complete Chemical Information, a web service that ranks chemical-gene-disease associations among biomedical articles.
  24. CaGeDB: Calcium Gene Database, connecting calcium signaling and associated diseases.
  25. cando.py: CANDO Python package for analysis of drug-proteome and drug-disease relationships.
  26. CancerLivER: database of gene expression and biomarker data of liver cancer.
  27. CancerResource: Cancer-relevant relationships of compounds and targets.
  28. CART: Chemical Annotation Retrieval Toolkit, retrieves annotations on biological effects of chemicals (part of Galaxy).
  29. Cell2Chem: Finds the relationship between species and biosynthetic compounds.
  30. CGINet: Graph convolutional network-based model for identifying chemical-gene interaction in an integrated multi-relational graph.
  31. Chem2Bio2RDF: Semantic framework for linking and data mining chemogenomic and systems chemical biology data.
  32. ChemAgora Portal: Provides functionalities to search into publicly available databases containing chemical information.
  33. ChemDIS: Chemical-Disease Inference System (uses CTD data via STITCH).
  34. Chemical Checker: Data aggregate that provides processed, harmonized, and integrated bioactivity data on small molecules.
  35. ChemIDplus: Chemical Identification dictionary and structure database.
  36. ChemiRs: Chemical Interactions with miRNAs.
  37. ChemProt: Annotated and predicted chemical-protein interactions.
  38. ChemSpider: Chemical structures and property predictions.
  39. ChiP-Enrich: Test ChIP-seq peak data for enrichment of biological pathways, Gene Ontology terms, and other types of gene sets.
  40. CKG-IMC: Deep learning model for predicting compound-protein interactions relevant to Alzheimer disease.
  41. ComptoxAI: Data infrastructure for computational and artificial intelligence research in predictive toxicology.
  42. covidAsk: Question answering system that combines biomedical text mining to provide answers to questions in real-time.
  43. CovMulNet19: Comprehensive COVID-19 network.
  44. CRdb: Chromatin Regulator database.
  45. CSgator: Compound Set Navigator: an integrated web platform for compound set analysis.
  46. DCABM-TCM: Database of Constituents Absorbed into Blood and Metabolites of Traditional Chinese Medicine.
  47. dcGO: Domain Centric GO, database of domain-centric ontologies on functions, phenotypes, and diseases.
  48. DDIT: Drug Disease Interaction Type, an online predictor that supports drug repositioning.
  49. DDMGD: Dragon Database for Methylated Genes and Diseases, provides associations between methylated genes and diseases.
  50. DDSS: Drug Discovery and Diagnostic Support System, ranks disease-associated genes in terms of causing less side-effects.
  51. DeepMPF: Deep Learning Framework for Identifying Drug-Target Interactions.
  52. DeepSeq2Drug: Deep learning proposed for drug repurposing for viral outbreaks.
  53. DeepR2cov: Deep representation on heterogeneous drug networks to discover agents treating the inflammatory response in COVID-19.
  54. DEER: Drug Environmental Effects and Regulation, explores the envrionmental effects on drug response.
  55. DEPOD: Dephosphorylation Database.
  56. DEXTER: Disease-Expression Relation Extraction from Text.
  57. dialogi: Text mining for drug-induced liver injury.
  58. DID: Drug-Indication Database, a database of structured drug-indication relations.
  59. DIGEP-Pred: Drug-Induced Gene Expression Profile Predictor, drug-induced changes of gene expression based on chemical structural formula.
  60. DisGeNET: Disease Gene Network, discovery platform integrating information on gene-disease associations.
  61. Disease-Diagnosis-Assistant: Short personalized ranked list of likely diseases for patient at a requested time-point.
  62. DISQOVER: Semantic search platform that aggregates data from disparate sources.
  63. DisSim: Disease Similarity, explores similar diseases and discovers relationships among diseases and therapeutic chemicals.
  64. DisSetSim: Tool for obtaining the similarity score of pair-wise disease sets.
  65. diXa: Data Infrastructure for Chemical Safety, a collection of high throughput toxicogenomics datasets produced by EU researchers.
  66. DLAD4U: Disease List Automatically Derived For You.
  67. DNetDB: Disease Network Database, explores disease relationships to provide insights into disease taxonomy and etiology.
  68. DPV: Drug Phenotype Vector: in silico predictions of drug-drug interactions.
  69. DrAFC: Drug Repositioning through Anti-Fibrosis Characteristic.
  70. DRSPRING: DRug Synergy PRediction by INtegrated Graph convolutional network.
  71. drug2gene: Knowledgebase that combines compound/drug-gene/protein information from publicly available databases.
  72. DrugBank: Bioinformatics resource that combines detailed drug data with target information.
  73. DrugDiseaseNet: R package for systems biology approach to discover novel therapeutic roles for established drugs.
  74. DrugnomeAI: Ensemble machine-learning framework for predicting druggability of candidate drug targets.
  75. Drug Voyager: Computational platform for exploring unintended drug action.
  76. Drugst.One: Platform that assists computational tools in becoming user-friendly, web-based utilities for drug repurposing.
  77. DSigDB: Drug Signatures Database, a collection of annotated drug/compound gene sets.
  78. DTINet: Drug-Target Interaction Network predictions.
  79. DynOVis: Visualization tool that capturse dynamic dose-over-time effects in biological networks.
  80. EDCMET Project: Metabolic effects of Endocrine Disrupting Chemicals: novel testing METhods and adverse outcome pathways.
  81. EDTox: R Shiny application to identify and prioritize endocrine disruptor chemicals.
  82. EPA CompTox Chemistry Dashboard: EPA's integration of diverse types of cheminformatics data ("External Links" to CTD).
  83. ETM-DB: Ethiopian Traditional Medicine-Database.
  84. ExHuMId: Exposome of Human Milk across India.
  85. exposomeShiny: Toolbox for exposome data analysis.
  86. GAD: Genetic Association Database, genetic association data from complex diseases and disorders.
  87. GADTI: Graph Autoencoder Approach for Drug-Target Interactions.
  88. Galaxy: A framework that makes advanced computational tools usable by non-experts.
  89. Ganfyd: Get A Note From Your Doctor, a collaborative medical wiki by medical professionals and invited non-medical experts.
  90. Gemma Phenocarta: Tools and database for meta-analysis of functional genomics data.
  91. GeneCodis: Web-based tool for finding significant concurrent annotations in gene lists.
  92. GeneEMBED: Gene-embedding-based evaluation of disease-gene relevance.
  93. Gene ORGANizer: Phenotype-based tool that links human genes to the body parts they affect.
  94. GeneSetDB: Meta-database integrating public databases focusing on human disease and pharmacology.
  95. GeneWeaver: System for the integration of functional genomics experiments.
  96. Genotify: Fast, lightweight gene lookup and summarization.
  97. GLADIATOR: Global Approach for Disease Associated Module Reconstruction.
  98. GPSy: Gene Prioritization System, a cross-species system that prioritizes genes for follow-up functional analyses.
  99. GSKB: Gene Set KnowledgeBase, a comprehensive knowledgebase for pathway analysis in mouse.
  100. GUILDify: Molecular networks underlying human diseases, their comorbidities and their druggable targets.
  101. Harmonizome: Collection of processed datasets about genes and proteins.
  102. HerDing: Herb recommendation system to treat diseases using genes and chemicals.
  103. HExpoChem: Information on diverse sources of chemicals with the aim to explore human health risk from chemical exposure.
  104. HeTDR: Drug Repositioning based on Heterogeneous networks and Text mining.
  105. HGDTI: Heterogeneous Graph Drug-Target Interaction neural network model.
  106. HOMER: Human Organ-specific Molecular Electronic Repository, defining human organ-specific genes/proteins.
  107. iBKH: integrative Biomedical Knowledge Hub.
  108. iDEP: integrated Differential Expression and Pathway analysis.
  109. iCTNet2: Integrated Complex Traits Networks, a Cytoscape app and database that builda networks by integrating biological interactions.
  110. iDrug: Computational pipeline to predict novel drug-disease and drug-target interactions based on a heterogeneous network.
  111. ILDgenDB: Interstitial Lung Disease Genetic Database.
  112. INSIdE nano: Integrated Network of Systems bIology Effects of NANOmaterials.
  113. INPUT: Intelligent Network Pharmacology Platform Unique for Traditional Chinese Medicine.
  114. iPCD: Integrated annotations for Programmed Cell Death.
  115. KDDANet: Known Drug-Disease Association Network.
  116. KGTK: Knowledge Graph Toolkit.
  117. Know2BIO: A comprehensive biomedical knowledge graph harmonizing heterogeneous database sources.
  118. LAERTES: Large-scale Adverse Effects Related to Treatment Evidence Standardization, assesses associations between drugs and health outcomes.
  119. LSQ: Linked SPARQL Queries dataset.
  120. Lynx: Database and knowledge extraction engine for integrative medicine.
  121. M2PP: Model to predict drug-targeted pathogenic proteins.
  122. MBROLE 3: Metabolites Biological Role, analysis of functional annotations of chemical compounds compiled from public databases.
  123. MetaADEDB: Meta Adverse Drug Events Database, a comprehensive computer-available adverse drug events database.
  124. methPLIER-CTD: novel DNA methylation analysis architecture used to analyze CTD dataset of lung cancer patients in the PRISM database.
  125. MetSigDis: Metabolic Signatures of Diseases.
  126. MINERVA: Molecular Interaction NEtwoRk VisuAlization, standalone webserver for visualization, exploration and management of molecular networks.
  127. MINERVA Plugin: MINERVA plugin for CandActBase.
  128. miRegulome: Integrated online repository that provides entire regulatory modules of a miRNA.
  129. MIRIAM: Provides a set of online services for the generation of unique and perennial identifiers for life science data.
  130. MGDHGS: Computational framework based on metabolite-gene-disease heterogeneous network to forecast potential associations.
  131. MMDB: Multimedia Monitoring Database, a harmonized chemical monitoring database.
  132. MOD-Finder: Multi-Omics Data set Finder.
  133. Monarch Initiative: Integrated platform of cross-species gene, disease, and phenotype data.
  134. Moving Targets: Exploring target and disease trends.
  135. MSeqDR: Mitochondrial disease Sequence Data Resource, collects and shares data for rare diseases, patients, and causative mutations.
  136. MultiPPIs: Multi-source molecular network representation learning model.
  137. MultiVERSE: Embedding of Monoplex, Multiplex, Heterogeneous, Multiplex-Heterogeneous and full Multiplex-Heterogeneous Networks.
  138. MycoCentral: Mycotoxin database.
  139. MyGene.info: API for integrated annotations for gene sets.
  140. NCBI Gene: NCBI's integrated database of genes, their sequences, and information.
  141. NCG: Network of Cancer Genes.
  142. NDEx: Network Data Exchange, users upload and distribute biological networks and pathway models (search with CTD).
  143. NeDRex: Integrative and interactive platform for network-based drug repurposing and disease module discovery.
  144. NetworkAnalyst: Visual analytics platform for comprehensive gene expression profiling & meta-analysis.
  145. NIF: Neuroscience Information Framework, supports neuroscience research into a collaborative framework.
  146. NPACT: Naturally occuring Plant-based Anticancerous Compound-Activity-Target Database, plant-derived natural compounds that exhibit anti-cancerous activity.
  147. NeuroMMSig: Neurodegenerative disease Multimodal Mechanistic Signatures, a web server for mechanism enrichment.
  148. NeurotoxKB: Environmental neurotoxicant knowledgebase.
  149. NOGEA: Network-Oriented Gene Entropy Approach.
  150. NRDTD: ncRNA Drug Targets Database.
  151. NTD-DR: Nonnegative Tensor Decomposition for Drug Repositioning.
  152. OOCDB: Organs-on-a-chip Database.
  153. PANACEA: Personalized Network-based Anti-Cancer Therapy Evaluation.
  154. Pathway Commons: Public pathway and interactions database.
  155. PCOSKB R2: PolyCystic Ovary Syndrome KnowledgeBase.
  156. PedAM: Pediatric Disease Annotations and Medicines.
  157. PGxLOD: Pharmacogenomic LOD.
  158. PharmacoMicrobiomics: Explores interactions between human-associated microbes and drugs by building a knowledgebase.
  159. PharmDB-K: Bio-pharmacological network database, offers comprehensive traditional Korean medicine-associated compound, drug, disease, and protein information.
  160. PharMeBINet: Pharmacological Medical Biochemical Network, heterogeneous database containing interconnected information on ADRs, diseases, drugs, and gene variations.
  161. PharmGKB: Pharmacogenomics Knowledgebase, curates information about drugs, diseases, and genes, including their variations and gene products.
  162. PharmOmics: Species- and tissue-specific drug signature database and online tool for drug repurposing.
  163. PharmKG: Multi-relational, attributed biomedical knowledge graph.
  164. PheKnowLator: Phenotype Knowledge Translator, construction of large-scale biomedical knowledge graphs from complex heterogeneous data.
  165. PhenoExam: R package and web application for the examination of phenotypes linked to genes and gene sets.
  166. PhenoHM: Human-Mouse Comparative Phenomics Server, tool to mine human and mouse orthologous phenotypes.
  167. phexpo: R package that provides bidirectional analyses approach covering relationships from chemicals to phenotypes and from phenotypes to chemicals.
  168. PHLeGrA: Pipeline for Hidden Variable Linked Graph Analytics, connects paths between drugs and adverse reactions.
  169. PISTON: Predicting drug Indications and Side effects using TOpic modeling and Natural language processing.
  170. PlaNet: Knowledge graph that reasons over population variability, disease biology, and drug chemistry.
  171. plasmiR: Database of experimentally verified circulating microRNAs with diagnostic and prognostic roles.
  172. Precision Medicine Corpus: A manually annotated corpus and related resources for information extraction in the biomedical domain.
  173. PPDB: Pathogenic Pathway Database for Periodontitis, manual collection of pathogenic pathways for periodontitis.
  174. PrimeKG: Precision Medicine Knowledge Graph, integration of 20 high-quality datasets, biorepositories, and ontologies.
  175. PsyGeNET: Psychiatric Disorders Gene Association Network, resource for exploring psychiatric diseases and their associated genes.
  176. PTMD: Post Translational Modifications associated with Diseases.
  177. PubChem: NCBI's integrated database of the biological activities of small molecules.
  178. RABC: Rheumatoid Arthritis Bioinformatics Center.
  179. RA-MAP: Rheumatoid Arthritis molecular map.
  180. RD-Connect: Rare Disease platform connecting databases, registries, biobanks, and clinical bioinformatics.
  181. REEL: Relation Extraction for Entity Linking, a named entity linking framework leveraging CTD's MEDIC and chemical vocabulary.
  182. Reactome: Manually curated and peer-reviewed pathway database.
  183. RefGene: Indexes of genes and antibodies.
  184. Research Analysis: Accelerating rate of scientific discovery through knowledge management.
  185. Retrosynthesis AI: Bioinformatics meets synthetic chemistry.
  186. RGD-MOET: Rat Genome Database Multi-Ontology Enrichment Tool.
  187. ROBOKOP: Reasoning Over Biomedical Objects linked in Knowledge-Oriented Pathways.
  188. SApredictor: Structural alert-based expert system for chemical toxicity prediction.
  189. SciCrunch: Researcher content management system designed for dynamic data.
  190. SCMFDD: Similarity Constrained Matrix Factorization method for the Drug-Disease association prediction.
  191. SIDD: Semantically Integrated Disease Database, establishes semantic associations among disease-related databases.
  192. SIENA: Semantic Enhancement of Datasets using Concept Recognition.
  193. SLAP: Semantic Link Association Prediction.
  194. SpiceRx: Integrated resource for the health impacts of culinary spices and herbs.
  195. Standigm ASK: AI-assisted platform tailored for identifying novel target genes associated with idiopathic pulmonary fibrosis.
  196. STITCH: Search Tool for Interactions of Chemicals, a database of known and predicted interactions between chemicals and proteins.
  197. SubGE-DDI: Subgraph Enhance model for Drug-Drug Interactions.
  198. SurfaceomeDB: Cancer-orientated database for genes encoding cell surface proteins.
  199. SympGAN: Symptom-Gene Associations Network.
  200. T3DB: Toxin and Toxin Target Database, a resource that combines detailed toxin data with comprehensive toxin target information.
  201. TarPred: Target Prediction, a web application for predicting therapeutic and side effect targets of chemical compounds.
  202. TBGA: semi-automatically annotated dataset for gene-disease associations extraction.
  203. TExAs: Tissue-specific Exposome Atlas.
  204. ThETA: Transcriptome-driven efficacy estimates for gene-based target discovery.
  205. ToppGene: Suite of tools for gene list enrichment and prioritization based on functional annotations and protein interactions network.
  206. Tox21 Enricher: Enriches toxicological characteristics in user's set of uploaded compounds.
  207. toxFlow: Web tools for Gene Set Variation Analysis (GSVA) and toxicity prediction.
  208. ToxAnalyzer: Webtool for analyzing CTD compounds.
  209. ToxicoDB: Database of curated toxicogenomics datasets.
  210. TOXNET: TOXNET.
  211. TOXPO: Toxicology Polymorphism Database.
  212. TransOrGAN: Molecular mapping of gene expression profiles in different rodent organ systems.
  213. Transformers-sklearn: Toolkit for medical language understanding with transformer-based models.
  214. Trove: Framework for weakly supervised entity classification using medical ontologies.
  215. UniProt: Comprehensive, high-quality and freely accessible resource of protein sequence and functional information.
  216. VARAdb: VARiation Annotation database for human.
  217. VarCards2: Variant- and gene-level annotation data to streamline genetic counselling for coding variants.
  218. WENDI: Web Engine for Non-obvious Drug Information.
  219. WhichGenes: Bioinformatics gene-set building tool.
  220. WITHDRAWN: Database of withdrawn and discontinued drugs that were pulled out of global markets due to safety concerns.