Unveiling new disease, pathway, and gene associations via multi-scale neural network.

ABSTRACT: Diseases involve complex modifications to the cellular machinery. The gene expression profile of the affected cells contains characteristic patterns linked to a disease. Hence, new biological knowledge about a disease can be extracted from these profiles, improving our ability to diagnose and assess disease risks. This knowledge can be used for drug re-purposing, or by physicians to evaluate a patient's condition and co-morbidity risk. Here, we consider differential gene expressions obtained by microarray technology for patients diagnosed with various diseases. Based on these data and cellular multi-scale organization, we aim at uncovering disease-disease, disease-gene and disease-pathway associations. We propose a neural network with structure based on the multi-scale organization of prot

SUBMITTER: Gaudelet T 

PROVIDER: S-EPMC7135208 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature