Inferring gene-phenotype associations via global protein complex network propagation
about
Integrative approaches for finding modular structure in biological networksBenchmarking human protein complexes to investigate drug-related systems and evaluate predicted protein complexesPrioritizing protein complexes implicated in human diseases by network optimizationWalking on a tissue-specific disease-protein-complex heterogeneous network for the discovery of disease-related protein complexesEnhancing systems medicine beyond genotype data by dynamic patient signatures: having information and using it tooTowards building a disease-phenotype knowledge base: extracting disease-manifestation relationship from literature.Gene prioritization for livestock diseases by data integration.A Bayesian analysis of the chromosome architecture of human disorders by integrating reductionist data.Tracing dynamic biological processes during phase transitionMicrobial community pattern detection in human body habitats via ensemble clustering framework.Inference of gene-phenotype associations via protein-protein interaction and orthology.dRiskKB: a large-scale disease-disease risk relationship knowledge base constructed from biomedical text.Ensemble positive unlabeled learning for disease gene identificationFinding trans-regulatory genes and protein complexes modulating meiotic recombination hotspots of human, mouse and yeast.Network propagation with dual flow for gene prioritization.A novel method for identifying disease associated protein complexes based on functional similarity protein complex networks.Network-based Phenome-Genome Association Prediction by Bi-Random Walk.Integrative analysis of human protein, function and disease networks.Effects of psychological stress on innate immunity and metabolism in humans: a systematic analysis.Using contrast patterns between true complexes and random subgraphs in PPI networks to predict unknown protein complexes.Guilt by rewiring: gene prioritization through network rewiring in genome wide association studies.Recent approaches to the prioritization of candidate disease genes.Transfer learning across ontologies for phenome-genome association prediction.Positive-unlabeled learning for disease gene identification.Prioritization of candidate disease genes by enlarging the seed set and fusing information of the network topology and gene expression.Predicting protein complexes using a supervised learning method combined with local structural information.A comprehensive dataset of genes with a loss-of-function mutant phenotype in Arabidopsis.
P2860
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P2860
Inferring gene-phenotype associations via global protein complex network propagation
description
2011 nî lūn-bûn
@nan
2011 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Inferring gene-phenotype associations via global protein complex network propagation
@ast
Inferring gene-phenotype associations via global protein complex network propagation
@en
type
label
Inferring gene-phenotype associations via global protein complex network propagation
@ast
Inferring gene-phenotype associations via global protein complex network propagation
@en
prefLabel
Inferring gene-phenotype associations via global protein complex network propagation
@ast
Inferring gene-phenotype associations via global protein complex network propagation
@en
P2093
P2860
P1433
P1476
Inferring gene-phenotype associations via global protein complex network propagation
@en
P2093
Chee-Keong Kwoh
See-Kiong Ng
P2860
P304
P356
10.1371/JOURNAL.PONE.0021502
P407
P577
2011-07-25T00:00:00Z