Harnessing big data for precision medicine: Infrastructures and applications

Kun Hsing Yu, Steven N. Hart, Rachel Goldfeder, Qiangfeng Cliff Zhang, Stephen C.J. Parker, Michael Snyder

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations

Abstract

Precision medicine is a health management approach that accounts for individual differences in genetic backgrounds and environmental exposures. With the recent advancements in high-throughput omics profiling technologies, collections of large study cohorts, and the developments of data mining algorithms, big data in biomedicine is expected to provide novel insights into health and disease states, which can be translated into personalized disease prevention and treatment plans. However, petabytes of biomedical data generated by multiple measurement modalities poses a significant challenge for data analysis, integration, storage, and result interpretation. In addition, patient privacy preservation, coordination between participating medical centers and data analysis working groups, as well as discrepancies in data sharing policies remain important topics of discussion. In this workshop, we invite experts in omics integration, biobank research, and data management to share their perspectives on leveraging big data to enable precision medicine.

Original languageEnglish (US)
Pages (from-to)635-639
Number of pages5
JournalPacific Symposium on Biocomputing
Volume0
Issue number212679
DOIs
StatePublished - 2017
Event22nd Pacific Symposium on Biocomputing, PSB 2017 - Kohala Coast, United States
Duration: Jan 4 2017Jan 8 2017

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computational Theory and Mathematics

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