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Integration of complex data sources to provide biologic insight into pulmonary vascular disease (2015 Grover Conference Series)

期刊

PULMONARY CIRCULATION
卷 6, 期 3, 页码 251-260

出版社

SAGE PUBLICATIONS INC
DOI: 10.1086/686995

关键词

pulmonary vascular disease; systems biology; computational network modeling; electronic medical record; biorepository; genomics

资金

  1. American Heart Association [13FTF16070002]
  2. Actelion Entelligence Young Investigator Award
  3. National Institutes of Health (NIH) [1P0 HL108800-01A1, 1U01 HL125212, HL096834, HL124021]
  4. Pulmonary Hypertension Association
  5. National Center for Research Resources [1S10RR025141-01]
  6. National Center for Advancing Translational Sciences/NIH [UL1TR000445]

向作者/读者索取更多资源

The application of complex data sources to pulmonary vascular diseases is an emerging and promising area of investigation. The use of -omics platforms, in silico modeling of gene networks, and linkage of large human cohorts with DNA biobanks are beginning to bear biologic insight into pulmonary hypertension. These approaches to high-throughput molecular phenotyping offer the possibility of discovering new therapeutic targets and identifying variability in response to therapy that can be leveraged to improve clinical care. Optimizing the methods for analyzing complex data sources and accruing large, well-phenotyped human cohorts linked to biologic data remain significant challenges. Here, we discuss two specific types of complex data sources-gene regulatory networks and DNA-linked electronic medical record cohorts-that illustrate the promise, challenges, and current limitations of these approaches to understanding and managing pulmonary vascular disease.

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