@inbook{2b1d196a490d4861ae614f7b56f7361b,
title = "Epistasis Detection Based on Epi-GTBN",
abstract = "Epistasis detection is a hot topic in bioinformatics due to its relevance to the detection of specific phenotypic traits and gene–gene interactions. Here, we present a step-by-step protocol to apply Epi-GTBN, a machine learning-based method based on genetic algorithm and Bayesian network to effectively mine the epistasis loci. Epi-GTBN utilizes the advantages of genetic algorithm that can achieve a global search and avoid falling into local optima incorporating it into the Bayesian network to obtain the best structure of the model. In this chapter, we describe an example of Epi-GTBN to help researchers to analyze the epistasis and gene–gene interactions of their own datasets and build the corresponding SNP–SNP network.",
keywords = "Bayesian network, Epi-GTBN, Epistasis loci mining, Genetic algorithm, Phenotypic traits",
author = "Xingjian Chen and Ka-Chun Wong",
year = "2021",
doi = "10.1007/978-1-0716-0947-7\_20",
language = "English",
isbn = "9781071609460",
series = "Methods in Molecular Biology",
publisher = "Humana Press",
pages = "325--335",
editor = "Ka-Chun Wong",
booktitle = "Epistasis",
address = "United States",
}