EpistasisRank and EpistasisKatz: interaction network centrality methods that integrate prior knowledge networks
Author(s) -
Saeid Parvandeh,
Brett A. McKinney
Publication year - 2018
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bty965
Subject(s) - centrality , computer science , network analysis , data science , artificial intelligence , knowledge management , mathematics , statistics , physics , quantum mechanics
An important challenge in gene expression analysis is to improve hub gene selection to enrich for biological relevance or improve classification accuracy for a given phenotype. In order to incorporate phenotypic context into co-expression, we recently developed an epistasis-expression network centrality method that blends the importance of gene-gene interactions (epistasis) and main effects of genes. Further blending of prior knowledge from functional interactions has the potential to enrich for relevant genes and stabilize classification.
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