References
- Robinette SL, Holmes E, Nicholson JK, Dumas ME. Genetic determinants of metabolism in health and disease: from biochemical genetics to genome-wide associations. Genome Med 2012;4:30
- Heidecker B, Hare JM. The use of transcriptomic biomarkers for personalized medicine. Heart Fail Rev 2007;12:1-11
- Liotta LA, Kohn EC, Petricoin EF. Clinical proteomics: personalized molecular medicine. JAMA 2001;286:2211-14
- Obama administration unveils “Big Data” initiative: announces $200 million in new R&D investments. The White House. Big Data Public Private Forum; Washington, DC: 2012. Available from: www. cordis.europa.eu [Last accessed 05 March 2013]
- Kreutz RP, Stanek EJ, Aubert R, et al. Impact of proton pump inhibitors on the effectiveness of clopidogrel after coronary stent placement: the clopidogrel Medco outcomes study. Pharmacotherapy 2010;30:787-96
- Dakshanamurthy S, Issa NT, Assefina S, et al. Predicting new indications for approved drugs using a proteochemometric method. J Med Chem 2012;55:6832-60
- Root DE, Kelley BP, Stockwell BR. Global analysis of large-scale chemical and biological experiments. Curr Opin Drug Discov Devel 2002;5(3):355-60
- Barabasi A, Oltvai Z. Network biology: understanding the cell’s functional organization. Nat Rev Genet 2004;5:101-13
- Lamb J, Crawford ED, Peck D, et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science 2006;313:1929-35
- ClinicalTrials.gov identifier: NCT00874562. Rapamycin in relapsed acute lymphoblastic leukemia. Available from: http://clinicaltrials.gov/show/NCT00874562
- Shi H, Hugo W, Kong X, et al. Acquired resistance and clonal evolution in melanoma during BRAF inhibitor therapy. Cancer Discov 2014;4:80-93
- Ganti S, Weiss R. Urine metabolomics for kidney cancer detection and biomarker discovery. Urol Oncol 2011;29:551-7
- Aboud O, Weiss R. New opportunities from the cancer metabolome. Clin Chem 2013;59:138-46
- Xu R, Wang Q. Toward creation of a cancer drug toxicity knowledge base: automatically extracting cancer drug–side effect relationships from the literature. J Am Med Inform Assoc 2014;21:90-6
- van Haagen HH, ’t Hoen PA, Mons B, Schultes EA. Generic information can retrieve known biological associations: implications for biomedical knowledge discovery. PLoS One 2013;8:e78665
- Gao Y, Holland R, Yu L. Quantitative proteomics for drug toxicity. Brief Funct Genomic Proteomic 2009;8:158-66
- Clayton TA, Lindon JC, Cloarec O, et al. Pharmaco-metabonomic phenotyping and personalized drug treatment. Nature 2006;440:1073-7
- Hanauer D, Rhodes D, Chinnaiyan A. Exploring clinical associations using ‘-omics’ based enrichment analyses. PLoS One 2009;4:e5203
- Castro VM, Clements CC, Murphy SN, et al. QT interval and antidepressant use: a cross sectional study of electronic health records. BMJ 2013;346:f288
- Lunshof J, Church G, Prainsack B. Raw personal data: providing access. Science 2014;343:373-4