Logic programming reveals alteration of key transcription factors in multiple myeloma.

ABSTRACT: Innovative approaches combining regulatory networks (RN) and genomic data are needed to extract biological information for a better understanding of diseases, such as cancer, by improving the identification of entities and thereby leading to potential new therapeutic avenues. In this study, we confronted an automatically generated RN with gene expression profiles (GEP) from a cohort of multiple myeloma (MM) patients and normal individuals using global reasoning on the RN causality to identify key-nodes. We modeled each patient by his or her GEP, the RN and the possible automatically detected repairs needed to establish a coherent flow of the information that explains the logic of the GEP. These repairs could represent cancer mutations leading to GEP variability. With this reasoning, unmeas

SUBMITTER: Miannay B 

PROVIDER: S-EPMC5569101 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature