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

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

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

http://www.wikidata.org/entity/Q34425461

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FHSA-SED: Two-Locus Model Detection for Genome-Wide Association Study with Harmony Search Algorithm Grid-based stochastic search for hierarchical gene-gene interactions in population-based genetic studies of common human diseases Weighted risk score-based multifactor dimensionality reduction to detect gene-gene interactions in nasopharyngeal carcinoma Mining pure, strict epistatic interactions from high-dimensional datasets: ameliorating the curse of dimensionality.ExSTraCS 2.0: Description and Evaluation of a Scalable Learning Classifier System.Bayesian neural networks for detecting epistasis in genetic association studies Genetic simulation tools for post-genome wide association studies of complex diseases A Multi-Core Parallelization Strategy for Statistical Significance Testing in Learning Classifier Systems.An efficiency analysis of high-order combinations of gene-gene interactions using multifactor-dimensionality reduction.Discovering causal interactions using Bayesian network scoring and information gain.gammaMAXT: a fast multiple-testing correction algorithm.Detecting gene-gene interactions using a permutation-based random forest method An information-gain approach to detecting three-way epistatic interactions in genetic association studies.Prioritizing tests of epistasis through hierarchical representation of genomic redundancies.CMDR based differential evolution identifies the epistatic interaction in genome-wide association studies.Functional networks inference from rule-based machine learning models.Niche harmony search algorithm for detecting complex disease associated high-order SNP combinations.A Comparative Study on Multifactor Dimensionality Reduction Methods for Detecting Gene-Gene Interactions with the Survival Phenotype.Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection.A classification and characterization of two-locus, pure, strict, epistatic models for simulation and detection.Multiobjective differential evolution-based multifactor dimensionality reduction for detecting gene-gene interactions.A fast and exhaustive method for heterogeneity and epistasis analysis based on multi-objective optimization.Heuristic identification of biological architectures for simulating complex hierarchical genetic interactions.Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach.A heuristic method for simulating open-data of arbitrary complexity that can be used to compare and evaluate machine learning methods.PMLB: a large benchmark suite for machine learning evaluation and comparison.A Powerful Gene-Based Test Accommodating Common and Low-Frequency Variants to Detect Both Main Effects and Gene-Gene Interaction Effects in Case-Control Studies.Heterogeneity Analysis and Diagnosis of Complex Diseases Based on Deep Learning Method.Collective feature selection to identify crucial epistatic variants.The search for gene-gene interactions in genome-wide association studies: challenges in abundance of methods, practical considerations, and biological interpretation.Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV).Continuous Endpoint Data Mining with ExSTraCS Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science Retooling Fitness for Noisy Problems in a Supervised Michigan-style Learning Classifier System The Role of Genetic Interactions in Neurodevelopmental Disorders FDHE-IW: A Fast Approach for Detecting High-Order Epistasis in Genome-Wide Case-Control Studies

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

http://www.wikidata.org/entity/Q34425461

description

2012 nî lūn-bûn

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2012 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած

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2012 թվականի հոտեմբերին հրատարակված գիտական հոդված

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2012年の論文

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GAMETES: a fast, direct algori ...... dels with random architectures

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GAMETES: a fast, direct algori ...... dels with random architectures

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GAMETES: a fast, direct algori ...... dels with random architectures

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Jeff Kiralis

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Jonathan M Fisher

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Nicholas A Sinnott-Armstrong

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Ryan J Urbanowicz

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Tamra Heberling

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CoaSim: a flexible environment for simulating genetic data under coalescent models.

XV.—The Correlation between Relatives on the Supposition of Mendelian Inheritance.

Missing heritability and strategies for finding the underlying causes of complex disease

Data simulation software for whole-genome association and other studies in human genetics.

Generating samples for association studies based on HapMap data.

SUP: an extension to SLINK to allow a larger number of marker loci to be simulated in pedigrees conditional on trait values.

A complete classification of epistatic two-locus models.

Bioinformatics challenges for genome-wide association studies.

Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer.

Epistasis: what it means, what it doesn't mean, and statistical methods to detect it in humans.

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23025260

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3605108

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