CEIT-JAX

Illuminating the Druggable Genome by Knowledge Graphs
Monarch Initiative: https://monarchinitiative.org/
Drug Central: https://drugcentral.org

Peter Robinson, M.D., M.Sc.
Professor
Computational Biology
The Jackson
Laboratory
Christopher Mungall, Ph.D.
Computer Research Scientist
Department Head, Molecular Ecosystems Biology
Lawrence
Berkeley National Laboratory
Tudor Oprea, M.D., Ph.D.
Professor
Chief, Translational Informatics Division
Internal Medicine Health Sciences Center
University of New Mexico

Contacts

Monarch Initiative: @MonarchInit
Translational Informatics: @translationalID

Overview

The CEIT-JAX group is led by Dr. Peter Robinson, who works in collaboration with Dr. Chris Mungall and Dr. Tudor Oprea to develop a knowledge graphs for elucidating further understanding of the IDG target proteins via collections of information from Monarch Initiative and Drug Central, to name a few. They intend to integrate these data into a semantically harmonized knowledge graph and then deploy machine learning algorithms with the intent to develop testable hypothesis for evaluating the functions of understudied kinases.

NIH grant number: 1U01 CA239108

Publications:

  1. Haendel M, Vasilevsky N, Unni D, Bologa C, Harris N, Rehm H, Hamosh A, Baynam G, Groza T, McMurry J, Dawkins H, Rath A, Thaxton C, Bocci G, Joachimiak MP, Köhler S, Robinson PN, Mungall C, Oprea TI. How many rare diseases are there? Nat Rev Drug Discov. 2020 Feb;19(2):77-78. doi: 10.1038/d41573-019-00180-y. PMID: 32020066; PMCID: PMC7771654.
  2. Bocci G, Benet LZ, Oprea TI. Can BDDCS illuminate targets in drug design? Drug Discov Today. 2019 Dec;24(12):2299-2306. doi: 10.1016/j.drudis.2019.09.021. Epub 2019 Oct 1. PMID: 31585170; PMCID: PMC7002033.
  3. Muratov EN , Amaro R , Andrade CH , Brown N , Ekins S , Fourches D , Isayev O , Kozakov D , Medina-Franco JL , Merz KM , Oprea TI , Poroikov V , Schneider G , Todd MH , Varnek A , Winkler DA , Zakharov AV , Cherkasov A , Tropsha A . A critical overview of computational approaches employed for COVID-19 drug discovery. Chem Soc Rev. 2021 Aug 21;50(16):9121-9151. doi: 10.1039/d0cs01065k. Epub 2021 Jul 2. PMID: 34212944; PMCID: PMC8371861.
  4. Caufield JH, Putman T, Schaper K, Unni DR, Hegde H, Callahan TJ, Cappelletti L, Moxon SAT, Ravanmehr V, Carbon S, Chan LE, Cortes K, Shefchek KA, Elsarboukh G, Balhoff J, Fontana T, Matentzoglu N, Bruskiewich RM, Thessen AE, Harris NL, Munoz-Torres MC, Haendel MA, Robinson PN, Joachimiak MP, Mungall CJ, Reese JT. KG-Hub-building and exchanging biological knowledge graphs. Bioinformatics. 2023 Jul 1;39(7):btad418. doi: 10.1093/bioinformatics/btad418. PMID: 37389415; PMCID: PMC10336030.
  5. Zhavoronkov A, Vanhaelen Q, Oprea TI. Will Artificial Intelligence for Drug Discovery Impact Clinical Pharmacology? Clin Pharmacol Ther. 2020 Apr;107(4):780-785. doi: 10.1002/cpt.1795. Epub 2020 Mar 3. PMID: 31957003; PMCID: PMC7158211.
  6. Cappelletti L, Fontana T, Casiraghi E, Ravanmehr V, Callahan TJ, Cano C, Joachimiak MP, Mungall CJ, Robinson PN, Reese J, Valentini G. GRAPE for fast and scalable graph processing and random-walk-based embedding. Nat Comput Sci. 2023 Jun;3(6):552-568. doi: 10.1038/s43588-023-00465-8. Epub 2023 Jun 26. PMID: 38177435; PMCID: PMC10768636.
  7. Bofill A, Jalencas X, Oprea TI, Mestres J. The human endogenous metabolome as a pharmacology baseline for drug discovery. Drug Discov Today. 2019 Sep;24(9):1806-1820. doi: 10.1016/j.drudis.2019.06.007. Epub 2019 Jun 19. PMID: 31226432; PMCID: PMC7748399.
  8. Elhadad MA, Jonasson C, Huth C, Wilson R, Gieger C, Matias P, Grallert H, Graumann J, Gailus-Durner V, Rathmann W, von Toerne C, Hauck SM, Koenig W, Sinner MF, Oprea TI, Suhre K, Thorand B, Hveem K, Peters A, Waldenberger M. Deciphering the Plasma Proteome of Type 2 Diabetes. Diabetes. 2020 Dec;69(12):2766-2778. doi: 10.2337/db20-0296. Epub 2020 Sep 14. PMID: 32928870; PMCID: PMC7679779.
  9. Cichońska A, Ravikumar B, Allaway RJ, Wan F, Park S, Isayev O, Li S, Mason M, Lamb A, Tanoli Z, Jeon M, Kim S, Popova M, Capuzzi S, Zeng J, Dang K, Koytiger G, Kang J, Wells CI, Willson TM; IDG-DREAM Drug-Kinase Binding Prediction Challenge Consortium; Oprea TI, Schlessinger A, Drewry DH, Stolovitzky G, Wennerberg K, Guinney J, Aittokallio T. Crowdsourced mapping of unexplored target space of kinase inhibitors. Nat Commun. 2021 Jun 3;12(1):3307. doi: 10.1038/s41467-021-23165-1. PMID: 34083538; PMCID: PMC8175708.
  10. Ravanmehr V, Blau H, Cappelletti L, Fontana T, Carmody L, Coleman B, George J, Reese J, Joachimiak M, Bocci G, Hansen P, Bult C, Rueter J, Casiraghi E, Valentini G, Mungall C, Oprea TI, Robinson PN. Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer. NAR Genom Bioinform. 2021 Dec 8;3(4):lqab113. doi: 10.1093/nargab/lqab113. PMID: 34888523; PMCID: PMC8652379.
  11. Reese J, Unni D, Callahan TJ, Cappelletti L, Ravanmehr V, Carbon S, Fontana T, Blau H, Matentzoglu N, Harris NL, Munoz-Torres MC, Robinson PN, Joachimiak MP, Mungall CJ. KG-COVID-19: a framework to produce customized knowledge graphs for COVID-19 response. bioRxiv [Preprint]. 2020 Aug 18:2020.08.17.254839. doi: 10.1101/2020.08.17.254839. Update in: Patterns (N Y). 2020 Nov 9;:100155. PMID: 32839776; PMCID: PMC7444288.
  12. Reese JT, Unni D, Callahan TJ, Cappelletti L, Ravanmehr V, Carbon S, Shefchek KA, Good BM, Balhoff JP, Fontana T, Blau H, Matentzoglu N, Harris NL, Munoz-Torres MC, Haendel MA, Robinson PN, Joachimiak MP, Mungall CJ. KG- COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response. Patterns (N Y). 2021 Jan 8;2(1):100155. doi: 10.1016/j.patter.2020.100155. Epub 2020 Nov 9. PMID: 33196056; PMCID: PMC7649624.
  13. Kropiwnicki E, Binder JL, Yang JJ, Holmes J, Lachmann A, Clarke DJB, Sheils T, Kelleher KJ, Metzger VT, Bologa CG, Oprea TI, Ma'ayan A. Getting Started with the IDG KMC Datasets and Tools. Curr Protoc. 2022 Jan;2(1):e355. doi: 10.1002/cpz1.355. PMID: 35085427; PMCID: PMC10789444.

Page reviewed on March 8, 2024