Improving the prediction of pharmacogenes using text-derived drug-gene relationships

Pacific Symposium on Biocomputing 2010, PSB 2010

Volumn , Issue , 2010, Pages 305-314

  Garten, Yael ^a   Tatonetti, Nicholas P ^a   Altman, Russ B ^b  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CO-OCCURRENCE; CRITICAL GOAL; CURATION; DRUG RESPONSE; HIGH QUALITY; KNOWLEDGE BASE; PHARMACOGENOMICS; SCIENTIFIC ARTICLES; TEXT MINING;

ALGORITHMS; DATA MINING; KNOWLEDGE BASED SYSTEMS;

GENES;

ALGORITHM; ARTICLE; BIOLOGY; DATA MINING; HUMAN; KNOWLEDGE BASE; PHARMACOGENETICS; STATISTICS; VALIDATION STUDY;

ALGORITHMS; COMPUTATIONAL BIOLOGY; DATA MINING; HUMANS; KNOWLEDGE BASES; PHARMACOGENETICS;

EID: 84873045376     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (29)

1. Evans & Mcleod. Pharmacogenomics - Drug Disposition, Drug Targets, and Side Effects. TV Engl J Med 348,538(2003).
2. Swen et al. Translating Pharmacogenomics: Challenges on the Road to the Clinic. PLoS Med 4, e209 (2007).
3. Weiss et al. Creating and evaluating genetic tests predictive of drug response. Nature reviews Drug discovery 7, 568 (2008).
4. Davis et al. The microeconomics of personalized medicine: today's challenge and tomorrow's promise. Nature reviews Drug discovery 8, 279 (2009).
5. Kirchheiner et al. Pharmacogenetics-based therapeutic recommendations - ready for clinical practice? Nature reviews Drug discovery 4, 639 (2005).
6. Goldstein et al. Pharmacogenetics goes genomic. Nat Rev Genet 4, 937 (2003).
7. Dollery, C.T. Beyond genomics. Clin Pharmacol Ther 82, 366-70 (2007).
8. McCarthy, M.I. et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat Rev Genet 9, 356-69 (2008).
9. Hansen, N.T., Brunak, S. & Altman, R.B. Generating genome-scale candidate gene lists for pharmacogenomics. Clin Pharmacol Ther 86, 183-9 (2009).
10. Klein, T.E. et al. Integrating genotype and phenotype information: an overview of the PharmGKB project. Pharmacogenetics Research Network and Knowledge Base. The Pharmacogenomics Journal 1, 167-70 (2001).
11. Wishart, D.S. et al. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Research 36, D901-6 (2008).
12. Milller, H.M., Kenny, E.E. & Sternberg, P.W. Textpresso: an ontology-based information retrieval and extraction system for biological literature. PLoS Biol 2, e309 (2004).
13. Hunter, L. & Cohen, K.B. Biomedical language processing: what's beyond PubMed? Mol Cell 21, 589-94 (2006).
14. Garten, Y. & Altman, R.B. Pharmspresso: a text mining tool for extraction of pharmacogenomic concepts and relationships from full text. BMC Bioinformatics 10 Suppl 2, S6 (2009).
15. Quosa | The total solution for efficiently managing and monitoring scientific literature, http://www.quosa.org. (2009).
16. Lage, K. et al. A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat Biotechnol 25, 309-16 (2007).
17. Hebert, C, Habimana, A., Elie, R. & Reader, T.A. Effects of chronic antidepressant treatments on 5-HT and NA transporters in rat brain: an autoradiographic study. Neurochem Int 38, 63-74 (2001).
18. Marcus, S.C., Hassan, M. & Olfson, M. Antidepressant switching among adherent patients treated for depression. Psychiatric services (Washington, DC) 60, 617-23 (2009).
19. Jones, S. et al. Docetaxel With Cyclophosphamide Is Associated With an Overall Survival Benefit Compared With Doxorubicin and Cyclophosphamide: 7-Year Follow-Up of US Oncology Research Trial 9735. JClin Oncol 27, 1177-83 (2009).
20. Neuvonen, P.J., Niemi, M. & Backman, J.T. Drug interactions with lipid-lowering drugs: mechanisms and clinical relevance. Clin Pharmacol Ther 80, 565-81 (2006).
21. Kreutz, R. et al. CYP3A5 genotype is associated with longer patient survival after kidney transplantation and long-term treatment with cyclosporine. The Pharmacogenomics Journal 8, 416-22 (2008).
22. Kreutz, R. et al. The effect of variable CYP3A5 expression on cyclosporine dosing, blood pressure and long-term graft survival in renal transplant patients. Pharmacogenetics 14, 665-71 (2004).
23. Fanta, S. et al. Pharmacogenetics of cyclosporine in children suggests an age-dependent influence of ABCB1 polymorphisms. Pharmacogenet Genomics 18, 77-90 (2008).
24. Ahlers, C.B., Fiszman, M., Demner-Fushman, D., Lang, F.-M. & Rindflesch, T.C. Extracting semantic predications from Medline citations for pharmacogenomics. Pacific Symposium on Biocomputing Pacific Symposium on Biocomputing, 209-20 (2007).
25. Poulter, G.L., Rubin, D.L., Altman, R.B. & Seoighe, C. MScanner: a classifier for retrieving Medline citations. BMC Bioinformatics (2008).
26. Rieder et al. Effect of VKORCl Haplotypes on Transcriptional Regulation and Warfarin Dose. N Engl J Med 352, 2285(2005).
27. Takeuchi et al. A genome-wide association study confirms VKORCl, CYP2C9, and CYP4F2 as principal genetic determinants of warfarin dose. PLoS Genet 5, el 000433 (2009).
28. Rajanayagam & Rajanayagam. Pharmacogenetics: Optimizing warfarin therapy. Nature Reviews Cardiology 6, 324 (2009).
29. Cooper, G.M. et al. A genome-wide scan for common genetic variants with a large influence on warfarin maintenance dose. Blood 112, 1022-7 (2008).