title: Inferring Genome-Wide Interaction Networks.
abstract: The inference of gene regulatory networks is an important process that contributes to a better understanding of biological and biomedical problems. These networks aim to capture the causal molecular interactions of biological processes and provide valuable information about normal cell physiology. In this book chapter, we introduce GNI methods, namely C3NET, RN, ARACNE, CLR, and MRNET and describe their components and working mechanisms. We present a comparison of the performance of these algorithms using the results of our previously published studies. According to the study results, which were obtained from simulated as well as expression data sets, the inference algorithm C3NET provides consistently better results than the other widely used methods.
authors.affiliation: Biomedical Engineering, Bahcesehir University, Istanbul, Turkey. gokmen.altay@eng.bahcesehir.edu.tr.
authors.forename: Gökmen
authors.initials: G
authors.lastname: Altay
authors.affiliation: Software Engineering, Bahcesehir University, Istanbul, Turkey.|Faculty of Medicine, Istanbul Bilim University, Istanbul, Turkey.
authors.forename: Onur
authors.initials: O
authors.lastname: Mendi
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D053263:Gene Regulatory Networks / Q000235:genetics*
keywords: Bioinformatics; Gene network inference; Gene network inference (GNI) algorithms