Differentially correlated genes in co-expression networks control phenotype transitions.

ABSTRACT:

Background

Co-expression networks are a tool widely used for analysis of "Big Data" in biology that can range from transcriptomes to proteomes, metabolomes and more recently even microbiomes. Several methods were proposed to answer biological questions interrogating these networks. Differential co-expression analysis is a recent approach that measures how gene interactions change when a biological system transitions from one state to another. Although the importance of differentially co-expressed genes to identify dysregulated pathways has been noted, their role in gene regulation is not well studied. Herein we investigated differentially co-expressed genes in a relatively simple mono-causal process (B lymphocyte deficiency) and in a complex multi-causal system (cervical cancer).

SUBMITTER: Thomas LD 

PROVIDER: S-EPMC5247791 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature