Biomedical Informatics on the Cloud: A Treasure Hunt for Advancing Cardiovascular Medicine

Circ Res. 2018 Apr 27;122(9):1290-1301. doi: 10.1161/CIRCRESAHA.117.310967.


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.

Keywords: cardiovascular disease; environment; informatics; machine learning; metadata.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Abstracting and Indexing
  • Big Data
  • Cardiology / methods
  • Cardiology / trends*
  • Cardiovascular Diseases* / genetics
  • Cloud Computing*
  • Computational Biology*
  • Data Mining
  • Databases as Topic
  • Gene Expression Profiling
  • Humans
  • Machine Learning
  • Metabolic Networks and Pathways
  • Phenotype
  • Precision Medicine / methods
  • Precision Medicine / trends
  • PubMed
  • Software
  • Workflow