A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules. - Wikidata - awgldk - TriplyDB

A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

http://www.wikidata.org/entity/Q33525507

about

Statistical Methods in Integrative Genomics Computational solutions to large-scale data management and analysis Biomarkers for combat-related PTSD: focus on molecular networks from high-dimensional data.Expression QTL modules as functional components underlying higher-order phenotypes.Using stochastic causal trees to augment Bayesian networks for modeling eQTL datasets.A new mapping method for quantitative trait loci of silkworm.Joint genetic analysis of gene expression data with inferred cellular phenotypes Genomewide multiple-loci mapping in experimental crosses by iterative adaptive penalized regression Simulating systems genetics data with SysGenSIM Stitching together multiple data dimensions reveals interacting metabolomic and transcriptomic networks that modulate cell regulation.High-order SNP combinations associated with complex diseases: efficient discovery, statistical power and functional interactions.Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses Exploring data from genetic association studies using Bayesian variable selection and the Dirichlet process: application to searching for gene × gene patterns.Identifying multi-layer gene regulatory modules from multi-dimensional genomic data.Discovery of multi-dimensional modules by integrative analysis of cancer genomic data.Use of pleiotropy to model genetic interactions in a population.Robust prediction of expression differences among human individuals using only genotype information.Statistical analysis reveals co-expression patterns of many pairs of genes in yeast are jointly regulated by interacting loci.Bridging the Gap between Genotype and Phenotype via Network Approaches.eQTL Epistasis - Challenges and Computational Approaches.GUESS-ing polygenic associations with multiple phenotypes using a GPU-based evolutionary stochastic search algorithm.Molecular network analysis enhances understanding of the biology of mental disorders.Two-stage genome-wide search for epistasis with implementation to Recombinant Inbred Lines (RIL) populations.Integrative multi-omics module network inference with Lemon-Tree Bayesian detection of expression quantitative trait loci hot spots.A Bayesian model for detection of high-order interactions among genetic variants in genome-wide association studies Symmetric Epistasis Estimation (SEE) and its application to dissecting interaction map of Plasmodium falciparum Module cover - a new approach to genotype-phenotype studies.Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules.Exploring dependence between categorical variables: Benefits and limitations of using variable selection within Bayesian clustering in relation to log-linear modelling with interaction terms Integrative genomics strategies to elucidate the complexity of drug response.JBASE: Joint Bayesian Analysis of Subphenotypes and Epistasis.POEM: Identifying Joint Additive Effects on Regulatory Circuits.Simultaneous grouping pursuit and feature selection over an undirected graph.A co-module approach for elucidating drug-disease associations and revealing their molecular basis.Bayesian Partition Models for Identifying Expression Quantitative Trait Loci.

P2860

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P2860

A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

http://www.wikidata.org/entity/Q33525507

description

2010 nî lūn-bûn

@nan

2010 թուականի Յունուարին հրատարակուած գիտական յօդուած

@hyw

2010 թվականի հունվարին հրատարակված գիտական հոդված

@hy

2010年の論文

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2010年論文

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2010年論文

@zh-hant

2010年論文

@zh-hk

2010年論文

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2010年論文

@zh-tw

2010年论文

@wuu

name

A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

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A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

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A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

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type

label

A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

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A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

@en

A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

@nl

prefLabel

A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

@ast

A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

@en

A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

@nl

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JOURNAL.PCBI.1000642

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PLOS Computational Biology

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A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.

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Eric E Schadt

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

Jun S Liu

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

Jun Zhu

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

Wei Zhang

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P2860

Variations in DNA elucidate molecular networks that cause disease

Multiple locus linkage analysis of genomewide expression in yeast.

Local regulatory variation in Saccharomyces cerevisiae

A comparison of normalization methods for high density oligonucleotide array data based on variance and bias

Functional discovery via a compendium of expression profiles.

Yeast Cbk1 and Mob2 activate daughter-specific genetic programs to induce asymmetric cell fates.

Mapping the genetic architecture of gene expression in human liver

Reversible jump Markov chain Monte Carlo computation and Bayesian model determination

Genetics of gene expression and its effect on disease

An integrative genomics approach to infer causal associations between gene expression and disease

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e1000642

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10.1371/JOURNAL.PCBI.1000642

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1

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20090830

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