AIMC Topic: Epistasis, Genetic

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Protocol for Epistasis Detection with Machine Learning Using GenEpi Package.

Methods in molecular biology (Clifton, N.J.)
To develop medical treatments and prevention, the association between disease and genetic variants needs to be identified. The main goal of genome-wide association study (GWAS) is to discover the underlying reason for vulnerability to disease and uti...

Deep Neural Networks for Epistatic Sequence Analysis.

Methods in molecular biology (Clifton, N.J.)
We report a step-by-step protocol to use pysster, a TensorFlow-based package for building deep neural networks on a broad range of epistatic sequences such as DNA, RNA, or annotated secondary structure sequences. Pysster provides users comprehensive ...

Brief Survey on Machine Learning in Epistasis.

Methods in molecular biology (Clifton, N.J.)
In biology, the term "epistasis" indicates the effect of the interaction of a gene with another gene. A gene can interact with an independently sorted gene, located far away on the chromosome or on an entirely different chromosome, and this interacti...

Multiobjective multifactor dimensionality reduction to detect SNP-SNP interactions.

Bioinformatics (Oxford, England)
MOTIVATION: Single-nucleotide polymorphism (SNP)-SNP interactions (SSIs) are popular markers for understanding disease susceptibility. Multifactor dimensionality reduction (MDR) can successfully detect considerable SSIs. Currently, MDR-based methods ...

CMDR based differential evolution identifies the epistatic interaction in genome-wide association studies.

Bioinformatics (Oxford, England)
MOTIVATION: Detecting epistatic interactions in genome-wide association studies (GWAS) is a computational challenge. Such huge numbers of single-nucleotide polymorphism (SNP) combinations limit the some of the powerful algorithms to be applied to det...

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

Bioinformatics (Oxford, England)
MOTIVATION: Gene-gene interaction (GGI) is one of the most popular approaches for finding and explaining the missing heritability of common complex traits in genome-wide association studies. The multifactor dimensionality reduction (MDR) method has b...

The Network Library: a framework to rapidly integrate network biology resources.

Bioinformatics (Oxford, England)
MOTIVATION: Much of the biological knowledge accumulated over the last decades is stored in different databases governed by various organizations and institutes. Integrating and connecting these vast knowledge repositories is an extremely useful meth...

Epistasis analysis using artificial intelligence.

Methods in molecular biology (Clifton, N.J.)
Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of exper...

Epistasis analysis using multifactor dimensionality reduction.

Methods in molecular biology (Clifton, N.J.)
Here we introduce the multifactor dimensionality reduction (MDR) methodology and software package for detecting and characterizing epistasis in genetic association studies. We provide a general overview of the method and then highlight some of the ke...