Exploring Integrative Analysis Using the BioMedical Evidence Graph.

ABSTRACT:

Purpose

The analysis of cancer biology data involves extremely heterogeneous data sets, including information from RNA sequencing, genome-wide copy number, DNA methylation data reporting on epigenetic regulation, somatic mutations from whole-exome or whole-genome analyses, pathology estimates from imaging sections or subtyping, drug response or other treatment outcomes, and various other clinical and phenotypic measurements. Bringing these different resources into a common framework, with a data model that allows for complex relationships as well as dense vectors of features, will unlock integrated data set analysis.

Methods

We introduce the BioMedical Evidence Graph (BMEG), a graph database and query engine for discovery and analysis of cancer biology. The BMEG is unique fr

SUBMITTER: Struck A 

PROVIDER: S-EPMC7049249 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature