Identifying essential genes in genome-scale metabolic models of consensus molecular subtypes of colorectal cancer.

ABSTRACT: Identifying essential targets in the genome-scale metabolic networks of cancer cells is a time-consuming process. The present study proposed a fuzzy hierarchical optimization framework for identifying essential genes, metabolites and reactions. On the basis of four objectives, the present study developed a framework for identifying essential targets that lead to cancer cell death and evaluating metabolic flux perturbations in normal cells that have been caused by cancer treatment. Through fuzzy set theory, a multiobjective optimization problem was converted into a trilevel maximizing decision-making (MDM) problem. We applied nested hybrid differential evolution to solve the trilevel MDM problem to identify essential targets in genome-scale metabolic models for five consensus molecular subt

SUBMITTER: Cheng CT 

PROVIDER: S-EPMC10198572 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature