Using empirical biological knowledge to infer regulatory networks from multi-omics data.

ABSTRACT:

Background

Integration of multi-omics data can provide a more complex view of the biological system consisting of different interconnected molecular components, the crucial aspect for developing novel personalised therapeutic strategies for complex diseases. Various tools have been developed to integrate multi-omics data. However, an efficient multi-omics framework for regulatory network inference at the genome level that incorporates prior knowledge is still to emerge.

Results

We present IntOMICS, an efficient integrative framework based on Bayesian networks. IntOMICS systematically analyses gene expression, DNA methylation, copy number variation and biological prior knowledge to infer regulatory networks. IntOMICS complements the missing biological prior knowledge by so-ca

SUBMITTER: Pacinkova A 

PROVIDER: S-EPMC9396869 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature