The potential of translational bioinformatics approaches for pharmacology research.
The field of bioinformatics has allowed the interpretation of massive amounts of biological data, ushering in the era of 'omics' to biomedical research. Its potential impact on pharmacology research is enormous and it has shown some emerging successes. A full realization of this potential, however, requires standardized data annotation for large health record databases and molecular data resources. Improved standardization will further stimulate the development of system pharmacology models, using translational bioinformatics methods. This new translational bioinformatics paradigm is highly complementary to current pharmacological research fields, such as personalized medicine, pharmacoepidemiology and drug discovery. In this review, I illustrate the application of transformational bioinformatics to research in numerous pharmacology subdisciplines.
Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN.|Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN.|Indiana Institute of Personalized Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
Lang
http://orcid.org/0000-0002-5334-8719
L
Li
D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D055808:Drug Discovery / Q000379:methods; D006801:Humans; D017891:Pharmacoepidemiology / Q000379:methods; D010600:Pharmacology / Q000379:methods*; D057285:Precision Medicine / Q000379:methods; D057170:Translational Research, Biomedical / Q000379:methods*
big data; clinical pharmacology; systems pharmacology; translational bioinformatics