Integrative methods for analyzing big data in precision medicine

Proteomics. 2016 Mar;16(5):741-58. doi: 10.1002/pmic.201500396.

Abstract

We provide an overview of recent developments in big data analyses in the context of precision medicine and health informatics. With the advance in technologies capturing molecular and medical data, we entered the area of "Big Data" in biology and medicine. These data offer many opportunities to advance precision medicine. We outline key challenges in precision medicine and present recent advances in data integration-based methods to uncover personalized information from big data produced by various omics studies. We survey recent integrative methods for disease subtyping, biomarkers discovery, and drug repurposing, and list the tools that are available to domain scientists. Given the ever-growing nature of these big data, we highlight key issues that big data integration methods will face.

Keywords: Big data; Bioinformatics; Integration methods; Personalized medicine.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Review

MeSH terms

  • Biomarkers / analysis*
  • Biomedical Research
  • Computational Biology / methods*
  • Drug Repositioning / methods*
  • Epigenomics / methods
  • Humans
  • Medical Informatics / methods*
  • Metabolomics / methods
  • Precision Medicine / methods*
  • Proteomics / methods
  • Transcriptome / genetics

Substances

  • Biomarkers