期刊
CIRCULATION RESEARCH
卷 122, 期 9, 页码 1290-1301出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/CIRCRESAHA.117.310967
关键词
cardiovascular disease; environment; informatics; machine learning; metadata
资金
- National Institutes of Health [U54 GM114833, U41 HG003751, U01 HL137159, R01 LM012087, R35 HL135772]
- T.C. Laubisch endowment at UCLA
In the digital age of cardiovascular medicine, the rate of biomedical discovery can be greatly accelerated by the guidance and resources required to unearth potential collections of knowledge. A unified computational platform leverages metadata to not only provide direction but also empower researchers to mine a wealth of biomedical information and forge novel mechanistic insights. This review takes the opportunity to present an overview of the cloud-based computational environment, including the functional roles of metadata, the architecture schema of indexing and search, and the practical scenarios of machine learning-supported molecular signature extraction. By introducing several established resources and state-of-the-art workflows, we share with our readers a broadly defined informatics framework to phenotype cardiovascular health and disease.
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