A forest-based approach to identifying gene and gene gene interactions.
about
FHSA-SED: Two-Locus Model Detection for Genome-Wide Association Study with Harmony Search AlgorithmReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data.A particle swarm based hybrid system for imbalanced medical data sampling.A forest-based feature screening approach for large-scale genome data with complex structures.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.Willows: a memory efficient tree and forest construction package.Detecting purely epistatic multi-locus interactions by an omnibus permutation test on ensembles of two-locus analyses.A genome-wide association analysis of Framingham Heart Study longitudinal data using multivariate adaptive splines.Memory management in genome-wide association studies.Identification of genes and haplotypes that predict rheumatoid arthritis using random forests.Detecting significant single-nucleotide polymorphisms in a rheumatoid arthritis study using random forests.Detecting Genes and Gene-gene Interactions for Age-related Macular Degeneration with a Forest-based ApproachRole for protein-protein interaction databases in human genetics.Search for the smallest random forest.The null distributions of test statistics in genomewide association studies.Maximal conditional chi-square importance in random forests.Discovering joint associations between disease and gene pairs with a novel similarity test.A genetic ensemble approach for gene-gene interaction identificationGene-gene interaction filtering with ensemble of filtersThe choice of null distributions for detecting gene-gene interactions in genome-wide association studiesEpistatic association mapping in homozygous crop cultivars.Comparative methods for association studies: a case study on metabolite variation in a Brassica rapa core collection.SNPs and other features as they predispose to complex disease: genome-wide predictive analysis of a quantitative phenotype for hypertension.Interactions among related genes of renin-angiotensin system associated with type 2 diabetes.A LASSO-based approach to analyzing rare variants in genetic association studies.Novel tree-based method to generate markers from rare variant dataDetecting essential and removable interactions in genome-wide association studies.Aggressive periodontitis defined by recursive partitioning analysis of immunologic factors.Importance measures for epistatic interactions in case-parent trios.eQTL Epistasis - Challenges and Computational Approaches.Propensity score-based nonparametric test revealing genetic variants underlying bipolar disorder.AprioriGWAS, a new pattern mining strategy for detecting genetic variants associated with disease through interaction effects.Statistical Analysis in Genetic Studies of Mental Illnesses.Comments on Fifty Years of Classification and Regression Trees.The use of classification trees for bioinformatics.Bagging survival tree procedure for variable selection and prediction in the presence of nonsusceptible patients.Nonparametric Covariate-Adjusted Association Tests Based on the Generalized Kendall's Tau().A gene-based information gain method for detecting gene-gene interactions in case-control studies.The distribution of circulating microRNA and their relation to coronary disease
P2860
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P2860
A forest-based approach to identifying gene and gene gene interactions.
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年学术文章
@wuu
2007年学术文章
@zh-cn
2007年学术文章
@zh-hans
2007年学术文章
@zh-my
2007年学术文章
@zh-sg
2007年學術文章
@yue
2007年學術文章
@zh
2007年學術文章
@zh-hant
name
A forest-based approach to identifying gene and gene gene interactions.
@ast
A forest-based approach to identifying gene and gene gene interactions.
@en
type
label
A forest-based approach to identifying gene and gene gene interactions.
@ast
A forest-based approach to identifying gene and gene gene interactions.
@en
prefLabel
A forest-based approach to identifying gene and gene gene interactions.
@ast
A forest-based approach to identifying gene and gene gene interactions.
@en
P2860
P356
P1476
A forest-based approach to identifying gene and gene gene interactions
@en
P2093
Heping Zhang
Meizhuo Zhang
P2860
P304
19199-19203
P356
10.1073/PNAS.0709868104
P407
P577
2007-11-28T00:00:00Z