A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.
about
Statistical Methods in Integrative GenomicsComputational solutions to large-scale data management and analysisBiomarkers 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 phenotypesGenomewide multiple-loci mapping in experimental crosses by iterative adaptive penalized regressionSimulating systems genetics data with SysGenSIMStitching 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 analysesExploring 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-TreeBayesian detection of expression quantitative trait loci hot spots.A Bayesian model for detection of high-order interactions among genetic variants in genome-wide association studiesSymmetric Epistasis Estimation (SEE) and its application to dissecting interaction map of Plasmodium falciparumModule 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 termsIntegrative 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
Q28385219-EADC99A9-EDF2-4DD8-B92F-C6308D7454D6Q28743172-B72CD265-D803-4A67-851E-2AC00F095092Q30849692-751D13A9-6BF1-4518-A014-818224F3274DQ33778435-780BF481-B5C6-4B49-B1CF-D77FDDA9E7BDQ33787492-7B090755-184C-42D3-8E59-B0E4C0FC5B68Q33806353-8AED3A9F-9959-4550-8AAC-CC0DC7BF477DQ33809402-C937C5B2-0E0A-4BE0-A7E2-9E4FC0024A1BQ33853199-D9550BEC-BF73-442F-8150-452D9A2F2490Q33954156-56199A6B-D73E-47C3-AA35-BA1BCEF34C32Q34234879-39BC2938-D858-4142-BCB8-D2BF84FEED77Q34247032-A582FC0D-7CBC-437C-996C-51FC4B426835Q34255194-53BAB697-1FA9-4D52-91C4-750070B025A8Q34360816-67176E1A-E508-46D6-9E51-2F97FFECBF24Q34366411-4972075D-9449-4665-BCED-A5B55BEF5E57Q34373598-D3F3D764-1401-47DF-8D30-F922B6FD4D4FQ34446684-FAD62DA7-E925-4508-B682-AE903DD4ADC9Q34649950-6644DD7D-D90D-423C-B771-107AF8E44717Q34650039-D9D37D28-6E22-45A8-AFC6-2A94755FB2D9Q34765467-F6803B99-8CAD-4143-8422-F403A8D7C608Q34765476-B825FF92-C24F-440C-B059-7383411B861AQ34945566-3C62932F-FE99-4791-BB18-9728BB9176F2Q34992037-BFEB1361-3AAB-4696-9115-D525356ED61AQ35533224-28F9B792-FCF8-45A0-BE9E-3E5222B2E9F0Q35560646-4F8C1DDF-F710-4D60-87EE-F03F78AFB26AQ35620404-21190105-856C-4B1E-9601-462AB7F7608BQ35852973-D2CE76D7-43D3-47DA-8367-5867BCFFD0ADQ36344913-8275D8C0-8A98-4D55-977D-555931A33F2CQ36677024-C0A626AD-D660-4721-8778-18E845C734A7Q36741214-8166722A-398D-439A-AFE0-4DF53AE4D750Q36976791-A0E3ED71-E273-463B-8942-E86694E79FF1Q37961088-2E169705-009D-4111-BEE9-DD5DE2217507Q38594069-3E9E5B13-AB04-446F-92B5-33471862D05EQ38871241-3239CADE-916D-4B22-9A58-7D4684ACFB1EQ41987830-4FC568E8-603E-47F3-B798-4CC1EF59871BQ42634026-D94845A9-4407-4E69-8E17-4F489CE655A3Q49271089-D570481A-F186-4A61-B4CA-31E70616000D
P2860
A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.
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
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
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
type
label
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
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
P2093
P2860
P1476
A Bayesian partition method for detecting pleiotropic and epistatic eQTL modules.
@en
P2093
P2860
P304
P356
10.1371/JOURNAL.PCBI.1000642
P577
2010-01-15T00:00:00Z