Year: 2024
Type: conference-paper
Abstract: Genetic regulatory networks represent the interactions present between genes and are a crucial step in understanding cellular physiology and complex pathological phenotypes. There are various methods to infer these networks from a set of genetic data. Among them, the MRNET method stands out, which is based on the mRMR feature selection algorithm. However, constructing genetic regulatory networks with MRNET is a computationally expensive process for large-scale datasets due to its cubic complexity concerning the number of genes. The objective of this work is to develop parallel versions of MRNET that can be executed on shared-memory parallel systems to accelerate its execution.
Authors: Javier Darriba, Jorge González
Institution: Universidade da Coruña
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4407418957