Epi-GTBN: an approach of epistasis mining based on genetic Tabu algorithm and Bayesian network

epiACO - a method for identifying epistasis based on ant Colony optimization algorithm

(2017) Yingxia Sun et al.   BioData Mining

A unified model based multifactor dimensionality reduction framework for detecting gene–gene interactions

(2016) Wenbao Yu et al.   BIOINFORMATICS

Discovering causal interactions using Bayesian network scoring and information gain

(2016) Zexian Zeng et al.   BMC BIOINFORMATICS

Identification of genetic interaction networks via an evolutionary algorithm evolved Bayesian network

(2016) Ruowang Li et al.   BioData Mining

Detecting gene-gene interactions using a permutation-based random forest method

(2016) Jing Li et al.   BioData Mining

LEAP: Biomarker Inference Through Learning and Evaluating Association Patterns

(2015) Xia Jiang et al.   GENETIC EPIDEMIOLOGY

Characterizing gene-gene interactions in a statistical epistasis network of twelve candidate genes for obesity

(2015) Rishika De et al.   BioData Mining

Learning Bayesian Networks with thebnlearnRPackage

(2015) Marco Scutari   Journal of Statistical Software

EPIQ--efficient detection of SNP-SNP epistatic interactions for quantitative traits

(2014) Y. Arkin et al.   BIOINFORMATICS

MACOED: a multi-objective ant colony optimization algorithm for SNP epistasis detection in genome-wide association studies

(2014) Peng-Jie Jing et al.   BIOINFORMATICS

AprioriGWAS, a New Pattern Mining Strategy for Detecting Genetic Variants Associated with Disease through Interaction Effects

(2014) Qingrun Zhang et al.   PLoS Computational Biology

EpiMiner: A three-stage co-information based method for detecting and visualizing epistatic interactions

(2013) Junliang Shang et al.   DIGITAL SIGNAL PROCESSING

Evaluation of Breast Cancer Susceptibility Using Improved Genetic Algorithms to Generate Genotype SNP Barcodes

(2013) Cheng-Hong Yang et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

An information-gain approach to detecting three-way epistatic interactions in genetic association studies

(2013) Ting Hu et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION

GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures

(2012) Ryan J Urbanowicz et al.   BioData Mining

Learning genetic epistasis using Bayesian network scoring criteria

(2011) Xia Jiang et al.   BMC BIOINFORMATICS

BOOST: A Fast Approach to Detecting Gene-Gene Interactions in Genome-wide Case-Control Studies

(2010) Xiang Wan et al.   AMERICAN JOURNAL OF HUMAN GENETICS

Predictive rule inference for epistatic interaction detection in genome-wide association studies

(2009) Xiang Wan et al.   BIOINFORMATICS

A random forest approach to the detection of epistatic interactions in case-control studies

(2009) Rui Jiang et al.   BMC BIOINFORMATICS

Epistatic Module Detection for Case-Control Studies: A Bayesian Model with a Gibbs Sampling Strategy

(2009) Wanwan Tang et al.   PLoS Genetics

SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies

(2008) Can Yang et al.   BIOINFORMATICS

A support vector machine approach for detecting gene-gene interaction

(2007) Shyh-Huei Chen et al.   GENETIC EPIDEMIOLOGY