about
Chemical genomics identifies small-molecule MCL1 repressors and BCL-xL as a predictor of MCL1 dependencyUnbiased reconstruction of a mammalian transcriptional network mediating pathogen responsesIdentification of transcriptional regulators in the mouse immune systemCandidate gene association studies: a comprehensive guide to useful in silico toolsGenetic architecture of ethanol-responsive transcriptome variation in Saccharomyces cerevisiae strains.Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individualsIntegrated DNA Copy Number and Gene Expression Regulatory Network Analysis of Non-small Cell Lung Cancer MetastasisAllele-specific behavior of molecular networks: understanding small-molecule drug response in yeastSPINE: SParse eIgengene NEtwork linking gene expression clusters in Dehalococcoides mccartyi to perturbations in experimental conditionsSparse Regression Based Structure Learning of Stochastic Reaction Networks from Single Cell Snapshot Time SeriesEvolutionary Conservation and Diversification of Puf RNA Binding Proteins and Their mRNA TargetsIntegrated enrichment analysis of variants and pathways in genome-wide association studies indicates central role for IL-2 signaling genes in type 1 diabetes, and cytokine signaling genes in Crohn's diseaseLearning transcriptional regulatory relationships using sparse graphical modelsExon-specific QTLs skew the inferred distribution of expression QTLs detected using gene expression array dataTrypanosome MKT1 and the RNA-binding protein ZC3H11: interactions and potential roles in post-transcriptional regulatory networks.Mitochondria associate with P-bodies and modulate microRNA-mediated RNA interference.Integrating external biological knowledge in the construction of regulatory networks from time-series expression data.Causal inference of gene regulation with subnetwork assembly from genetical genomics data.Identification of ovarian cancer driver genes by using module network integration of multi-omics data.Joint analysis of functional genomic data and genome-wide association studies of 18 human traits.A bayesian framework that integrates heterogeneous data for inferring gene regulatory networksIntegrating functional data to prioritize causal variants in statistical fine-mapping studies.Multiple in silico tools predict phenotypic manifestations in congenital thrombotic thrombocytopenic purpura.A differential wiring analysis of expression data correctly identifies the gene containing the causal mutation.Statistical estimation of correlated genome associations to a quantitative trait networkInferring the transcriptional landscape of bovine skeletal muscle by integrating co-expression networks.Understanding gene sequence variation in the context of transcription regulation in yeast.Tom20 mediates localization of mRNAs to mitochondria in a translation-dependent manner.Toward the dynamic interactome: it's about time.Advances in genetical genomics of plants.Fungal regulatory evolution: cis and trans in the balance.Network analysis identifies ELF3 as a QTL for the shade avoidance response in ArabidopsisData-driven assessment of eQTL mapping methods.Polymorphic cis- and trans-regulation of human gene expression.Functional annotation signatures of disease susceptibility loci improve SNP association analysis.Genetics. Systems genetics.A machine learning pipeline for quantitative phenotype prediction from genotype data.Integrative analysis of low- and high-resolution eQTLUsing stochastic causal trees to augment Bayesian networks for modeling eQTL datasets.Co-regulatory expression quantitative trait loci mapping: method and application to endometrial cancer.
P2860
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P2860
description
2009 nî lūn-bûn
@nan
2009 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
Learning a prior on regulatory potential from eQTL data
@ast
Learning a prior on regulatory potential from eQTL data
@en
Learning a prior on regulatory potential from eQTL data
@en-gb
Learning a prior on regulatory potential from eQTL data
@nl
type
label
Learning a prior on regulatory potential from eQTL data
@ast
Learning a prior on regulatory potential from eQTL data
@en
Learning a prior on regulatory potential from eQTL data
@en-gb
Learning a prior on regulatory potential from eQTL data
@nl
prefLabel
Learning a prior on regulatory potential from eQTL data
@ast
Learning a prior on regulatory potential from eQTL data
@en
Learning a prior on regulatory potential from eQTL data
@en-gb
Learning a prior on regulatory potential from eQTL data
@nl
P2860
P50
P3181
P1433
P1476
Learning a prior on regulatory potential from eQTL data
@en
P2093
Nevan J Krogan
P2860
P304
P3181
P356
10.1371/JOURNAL.PGEN.1000358
P407
P577
2009-01-01T00:00:00Z