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SNP interaction detection with Random Forests in high-dimensional genetic data

SNP interaction detection with Random Forests in high-dimensional genetic data

http://www.wikidata.org/entity/Q34336861

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Publication Bias in Methodological Computational Research Evaluation of potential novel variations and their interactions related to bipolar disorders: analysis of genome-wide association study data Gene-environment interactions in genome-wide association studies: current approaches and new directions ReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data.Combining techniques for screening and evaluating interaction terms on high-dimensional time-to-event data.Genetic Adaptation to Climate in White Spruce Involves Small to Moderate Allele Frequency Shifts in Functionally Diverse Genes.Modeling X Chromosome Data Using Random Forests: Conquering Sex Bias A forest-based feature screening approach for large-scale genome data with complex structures.IGENT: efficient entropy based algorithm for genome-wide gene-gene interaction analysis.A comparison of internal model validation methods for multifactor dimensionality reduction in the case of genetic heterogeneity.A system-level pathway-phenotype association analysis using synthetic feature random forest.Exploiting SNP correlations within random forest for genome-wide association studies Research on single nucleotide polymorphisms interaction detection from network perspective Do little interactions get lost in dark random forests?SNP-SNP Interaction Analysis on Soybean Oil Content under Multi-Environments.Genome-wide QTL mapping of saltwater tolerance in sibling species of Anopheles (malaria vector) mosquitoes KNN-MDR: a learning approach for improving interactions mapping performances in genome wide association studies.Detecting gene-gene interactions using a permutation-based random forest method Identification of genetic interaction networks via an evolutionary algorithm evolved Bayesian network.Evaluation of genetic risk score models in the presence of interaction and linkage disequilibrium.National Veterans Health Administration inpatient risk stratification models for hospital-acquired acute kidney injury.A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology.A Weighted Random Forests Approach to Improve Predictive Performance.Letter to the Editor: On the term 'interaction' and related phrases in the literature on Random Forests.Extending the Distributed Lag Model framework to handle chemical mixtures.Prediction and identification of the effectors of heterotrimeric G proteins in rice (Oryza sativa L.).Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models.Identification of immune correlates of protection in Shigella infection by application of machine learning.Predicting attention-deficit/hyperactivity disorder severity from psychosocial stress and stress-response genes: a random forest regression approach Machine Learning and Radiogenomics: Lessons Learned and Future Directions.Statistically reinforced machine learning for nonlinear patterns and variable interactions The use of random forests modelling to detect yeast-mannan sensitive bacterial changes in the broiler cecum Transition-transversion encoding and genetic relationship metric in ReliefF feature selection improves pathway enrichment in GWAS Using recursive feature elimination in random forest to account for correlated variables in high dimensional data

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SNP interaction detection with Random Forests in high-dimensional genetic data

http://www.wikidata.org/entity/Q34336861

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2012 nî lūn-bûn

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2012 թուականի Յուլիսին հրատարակուած գիտական յօդուած

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2012 թվականի հուլիսին հրատարակված գիտական հոդված

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2012年の論文

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2012年論文

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2012年論文

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2012年論文

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2012年論文

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2012年論文

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2012年论文

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name

SNP interaction detection with Random Forests in high-dimensional genetic data

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SNP interaction detection with Random Forests in high-dimensional genetic data

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SNP interaction detection with Random Forests in high-dimensional genetic data

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SNP interaction detection with Random Forests in high-dimensional genetic data

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SNP interaction detection with Random Forests in high-dimensional genetic data

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SNP interaction detection with Random Forests in high-dimensional genetic data

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SNP interaction detection with Random Forests in high-dimensional genetic data

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SNP interaction detection with Random Forests in high-dimensional genetic data

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SNP interaction detection with Random Forests in high-dimensional genetic data

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1471-2105-13-164

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BMC Bioinformatics

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SNP interaction detection with Random Forests in high-dimensional genetic data

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Colin L Colby

http://www.w3.org/2001/XMLSchema#string

Joanna M Biernacka

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Marianne Huebner

http://www.w3.org/2001/XMLSchema#string

Robert R Freimuth

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Xin Wang

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P2860

Finding the missing heritability of complex diseases

A comprehensive review of genetic association studies

A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase

Genome-wide association studies for complex traits: consensus, uncertainty and challenges

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

Screening large-scale association study data: exploiting interactions using random forests

Gene selection and classification of microarray data using random forest.

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

HapSim: a simulation tool for generating haplotype data with pre-specified allele frequencies and LD coefficients.

Power of multifactor dimensionality reduction for detecting gene-gene interactions in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneity.

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13

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Mariza de Andrade

Stacey J Winham

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