ANIMA: Association network integration for multiscale analysis.

ABSTRACT: Contextual functional interpretation of -omics data derived from clinical samples is a classical and difficult problem in computational systems biology. The measurement of thousands of data points on single samples has become routine but relating 'big data' datasets to the complexities of human pathobiology is an area of ongoing research. Complicating this is the fact that many publicly available datasets use bulk transcriptomics data from complex tissues like blood. The most prevalent analytic approaches derive molecular 'signatures' of disease states or apply modular analysis frameworks to the data. Here we describe ANIMA (association network integration for multiscale analysis), a network-based data integration method using clinical phenotype and microarray data as inputs. ANIMA is impl

SUBMITTER: Deffur A 

PROVIDER: S-EPMC6134339 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature