Detecting epistatic interactions contributing to quantitative traits.
about
Information-theoretic gene-gene and gene-environment interaction analysis of quantitative traitsUGMDR: a unified conceptual framework for detection of multifactor interactions underlying complex traits.Principal interactions analysis for repeated measures data: application to gene-gene and gene-environment interactionsGenetics of GABAergic signaling in nicotine and alcohol dependence.Practical and theoretical considerations in study design for detecting gene-gene interactions using MDR and GMDR approachesGene-gene interactions among CHRNA4, CHRNB2, BDNF, and NTRK2 in nicotine dependence.A combinatorial approach to detecting gene-gene and gene-environment interactions in family studies.A generalized combinatorial approach for detecting gene-by-gene and gene-by-environment interactions with application to nicotine dependence.Novel likelihood ratio tests for screening gene-gene and gene-environment interactions with unbalanced repeated-measures data.Genetic associations in preterm birth: a primer of marker selection, study design, and data analysis.The use of the restricted partition method with case-control data.Detecting epistatic interactions contributing to human gene expression using the CEPH family dataThe challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases.Two-stage two-locus models in genome-wide association.Detection of gene x gene interactions in genome-wide association studies of human population data.Gene x gene and gene x environment interactions for complex disordersAlternative contingency table measures improve the power and detection of multifactor dimensionality reductionThe effect of alternative permutation testing strategies on the performance of multifactor dimensionality reduction.MegaSNPHunter: a learning approach to detect disease predisposition SNPs and high level interactions in genome wide association study.A random forest approach to the detection of epistatic interactions in case-control studies.Epistatic module detection for case-control studies: a Bayesian model with a Gibbs sampling strategy.Detecting purely epistatic multi-locus interactions by an omnibus permutation test on ensembles of two-locus analyses.Finding unique filter sets in PLATO: a precursor to efficient interaction analysis in GWAS data.Power and false-positive rates for the restricted partition method (RPM) in a large candidate gene data set.Evaluating epistatic interaction signals in complex traits using quantitative traits.Identifying main effects and epistatic interactions from large-scale SNP data via adaptive group LassoA general framework for formal tests of interaction after exhaustive search methods with applications to MDR and MDR-PDT.AntEpiSeeker: detecting epistatic interactions for case-control studies using a two-stage ant colony optimization algorithm.Prioritizing GWAS results: A review of statistical methods and recommendations for their application.Analysis pipeline for the epistasis search - statistical versus biological filtering.Bioinformatics challenges for genome-wide association studies.A novel adaptive method for the analysis of next-generation sequencing data to detect complex trait associations with rare variants due to gene main effects and interactions.Grid-based stochastic search for hierarchical gene-gene interactions in population-based genetic studies of common human diseasesThe choice of null distributions for detecting gene-gene interactions in genome-wide association studiesAnalysis of gene-gene interactions.Empirical Statistical Power for Testing Multilocus Genotypic Effects under Unbalanced Designs Using a Gibbs Sampler.Identification of interacting genes in genome-wide association studies using a model-based two-stage approachPerformance analysis of novel methods for detecting epistasis.Multivariate dimensionality reduction approaches to identify gene-gene and gene-environment interactions underlying multiple complex traits.A Simple and Computationally Efficient Approach to Multifactor Dimensionality Reduction Analysis of Gene-Gene Interactions for Quantitative Traits.
P2860
Q24654810-1978CB54-CCCA-4A77-99B6-A705F5D8F144Q27323246-1954BC46-9F4C-416E-9B1C-4632C6689937Q28387257-BD02B332-AC0D-4EFA-852E-0F316790A8E0Q30417644-49F4A2C3-1DA1-4192-9F43-752169758504Q30432971-BC9965D4-5BF7-4AC3-812D-EF66990FA96FQ30437713-555691FC-974A-41DD-AFBA-AC96BC8F17C7Q30439847-A5549D11-52FF-4138-BE1B-7688FBA36BA9Q30443642-3A94FBB9-2E92-4228-99D3-BB5C2EA84B04Q30651509-BC2BFD40-14BB-4616-B1BF-488E33CD077BQ31074202-D4A64741-2EC6-4D6A-9C6E-F2043AA300E1Q31098276-79DE765D-EE04-4DED-8B64-7766EBA92EE5Q31154941-71C8CE2B-485F-4FE0-85F0-7D9F6DABB315Q33240664-8A71A189-00EF-4FF5-B010-0E70920988F9Q33258470-FB767AB9-73C7-4AB1-B487-906965B4046BQ33272417-4E7189D1-BB9A-4A9D-9DC5-CCC4EAAC1DBAQ33333057-391FE7E5-F88A-41A2-BE3F-FACDA2DA9AFAQ33335357-DB603910-8426-48C2-8428-5244816DAE97Q33396570-0980511B-0E79-4A20-9069-7B4E461DDF2BQ33398791-FA765ED5-F772-43B2-91FD-B06A19E8D1ABQ33407925-7F402D70-B731-4241-9599-59EA6F607BCFQ33438429-5EF366E7-F0BD-49F1-A507-5C05F5337CC9Q33504429-56ECEE95-B71C-4E74-869E-60272E18830DQ33515833-E41322A4-7EC1-46B8-95D0-88A018C73FD1Q33519373-B29B6F5B-D4EC-4F74-B8F6-73F43824E598Q33519387-D0BF0A0B-2D6E-4A10-AC48-85327E4DE807Q33528187-73DA679C-1CA3-4A76-9697-AECC627457C7Q33534676-F159A172-9D74-40D5-8D75-D216324BD3CBQ33567152-3A513032-0385-4A5E-A273-2D63427C21B5Q33571786-E479E8F8-E5E1-476C-9282-D9C1F21A9196Q33574677-A6BB1CF9-0277-4398-985E-AAF3485FB613Q33647983-444A5414-BE78-44D8-BF9F-FF16C8922953Q33728642-779AE32E-F375-4BE6-A3AE-CE2BFCCDA621Q33743754-FF91B0D6-59F5-4EEF-AF6D-32993C72C107Q33826953-F79F8707-A835-4817-B540-5C459154A976Q33860591-CFEBA1FD-B87C-455B-BF2E-EFF25D39F3BDQ33884534-A4A10FF0-11B1-4F78-BBFE-503347CACE04Q34071820-62D7CC45-122B-4B3F-9126-68D4DE5FB7F3Q34102036-342FA048-5124-43F8-B01E-893F9928B14FQ34258237-6C8944E7-AED3-4054-8738-8DB365362B57Q34353866-5A21D4B8-38AA-4C7B-B5DE-07BFE4A39292
P2860
Detecting epistatic interactions contributing to quantitative traits.
description
2004 nî lūn-bûn
@nan
2004年の論文
@ja
2004年論文
@yue
2004年論文
@zh-hant
2004年論文
@zh-hk
2004年論文
@zh-mo
2004年論文
@zh-tw
2004年论文
@wuu
2004年论文
@zh
2004年论文
@zh-cn
name
Detecting epistatic interactions contributing to quantitative traits.
@ast
Detecting epistatic interactions contributing to quantitative traits.
@en
type
label
Detecting epistatic interactions contributing to quantitative traits.
@ast
Detecting epistatic interactions contributing to quantitative traits.
@en
prefLabel
Detecting epistatic interactions contributing to quantitative traits.
@ast
Detecting epistatic interactions contributing to quantitative traits.
@en
P2093
P356
P1433
P1476
Detecting epistatic interactions contributing to quantitative traits.
@en
P2093
Robert Culverhouse
Tsvika Klein
William Shannon
P304
P356
10.1002/GEPI.20006
P577
2004-09-01T00:00:00Z