| Literature DB >> 29700073 |
Peipei Ping1,2,3,4, Henning Hermjakob5,6, Jennifer S Polson5,2, Panagiotis V Benos7,8, Wei Wang5,4.
Abstract
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.Entities:
Keywords: cardiovascular disease; environment; informatics; machine learning; metadata
Mesh:
Year: 2018 PMID: 29700073 PMCID: PMC6192708 DOI: 10.1161/CIRCRESAHA.117.310967
Source DB: PubMed Journal: Circ Res ISSN: 0009-7330 Impact factor: 17.367