Modeling Basins of Attraction for Breast Cancer Using Hopfield Networks.

ABSTRACT: Cancer is a genetic disease for which traditional treatments cause harmful side effects. After two decades of genomics technological breakthroughs, personalized medicine is being used to improve treatment outcomes and mitigate side effects. In mathematical modeling, it has been proposed that cancer matches an attractor in Waddington's epigenetic landscape. The use of Hopfield networks is an attractive modeling approach because it requires neither previous biological knowledge about protein-protein interactions nor kinetic parameters. In this report, Hopfield network modeling was used to analyze bulk RNA-Seq data of paired breast tumor and control samples from 70 patients. We characterized the control and tumor attractors with respect to their size and potential energy and correlated the Eu

SUBMITTER: Conforte AJ 

PROVIDER: S-EPMC7154169 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature