Prioritizing candidate disease genes by network-based boosting of genome-wide association data. - Wikidata - awgldk - TriplyDB

Prioritizing candidate disease genes by network-based boosting of genome-wide association data.

Prioritizing candidate disease genes by network-based boosting of genome-wide association data.

http://www.wikidata.org/entity/Q33887815

about

A census of human soluble protein complexes Understanding Genotype-Phenotype Effects in Cancer via Network Approaches Fundamentals of protein interaction network mapping Regulatory network inferred using expression data of small sample size: application and validation in erythroid system Integrative approaches for finding modular structure in biological networks The shortest path is not the one you know: application of biological network resources in precision oncology research Applications of comparative evolution to human disease genetics Exome sequencing links corticospinal motor neuron disease to common neurodegenerative disorders The clustering of functionally related genes contributes to CNV-mediated disease PARP9 and PARP14 cross-regulate macrophage activation via STAT1 ADP-ribosylation Systems biology approach reveals genome to phenome correlation in type 2 diabetes Prediction and validation of gene-disease associations using methods inspired by social network analyses Towards structural systems pharmacology to study complex diseases and personalized medicine SemFunSim: a new method for measuring disease similarity by integrating semantic and gene functional association Protein interaction networks reveal novel autism risk genes within GWAS statistical noise Prioritizing causal disease genes using unbiased genomic features Quantifying the impact and extent of undocumented biomedical synonymy The Growing Importance of CNVs: New Insights for Detection and Clinical Interpretation STRING v9.1: protein-protein interaction networks, with increased coverage and integration DistiLD Database: diseases and traits in linkage disequilibrium blocks A Nondegenerate Code of Deleterious Variants in Mendelian Loci Contributes to Complex Disease Risk Whole-exome SNP array identifies 15 new susceptibility loci for psoriasis.GeneSense: a new approach for human gene annotation integrated with protein-protein interaction networks.Gene, pathway and network frameworks to identify epistatic interactions of single nucleotide polymorphisms derived from GWAS data.Chapter 2: Data-driven view of disease biology Network-based multiple sclerosis pathway analysis with GWAS data from 15,000 cases and 30,000 controls.Discover context-specific combinatorial transcription factor interactions by integrating diverse ChIP-Seq data sets Network analysis of GWAS data Interactive Big Data Resource to Elucidate Human Immune Pathways and Diseases.Improving disease gene prioritization by comparing the semantic similarity of phenotypes in mice with those of human diseases.MUFFINN: cancer gene discovery via network analysis of somatic mutation data.Large-Scale Public Transcriptomic Data Mining Reveals a Tight Connection between the Transport of Nitrogen and Other Transport Processes in Arabidopsis.Fusing literature and full network data improves disease similarity computation.Constructing Bayesian networks by integrating gene expression and copy number data identifies NLGN4Y as a novel regulator of prostate cancer progression.A transcription factor hierarchy defines an environmental stress response network HGCS: an online tool for prioritizing disease-causing gene variants by biological distance RIDDLE: reflective diffusion and local extension reveal functional associations for unannotated gene sets via proximity in a gene network.A novel network regularized matrix decomposition method to detect mutated cancer genes in tumour samples with inter-patient heterogeneity.An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.MORPHIN: a web tool for human disease research by projecting model organism biology onto a human integrated gene network.

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P2860

Prioritizing candidate disease genes by network-based boosting of genome-wide association data.

http://www.wikidata.org/entity/Q33887815

description

2011 nî lūn-bûn

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2011 թուականի Մայիսին հրատարակուած գիտական յօդուած

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2011 թվականի մայիսին հրատարակված գիտական հոդված

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2011年の論文

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2011年論文

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2011年論文

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2011年論文

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2011年論文

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2011年論文

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2011年论文

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name

Prioritizing candidate disease ...... genome-wide association data.

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Prioritizing candidate disease ...... genome-wide association data.

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type

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Prioritizing candidate disease ...... genome-wide association data.

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Prioritizing candidate disease ...... genome-wide association data.

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Prioritizing candidate disease ...... genome-wide association data.

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Prioritizing candidate disease ...... genome-wide association data.

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Genome Research

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Prioritizing candidate disease ...... f genome-wide association data

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Insuk Lee

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Jung Eun Shim

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Peggy I Wang

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U Martin Blom

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P2860

Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease

Identification of host proteins required for HIV infection through a functional genomic screen

A genome-scale RNAi screen for Oct4 modulators defines a role of the Paf1 complex for embryonic stem cell identity

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

Systematic discovery of nonobvious human disease models through orthologous phenotypes

GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function

A genome-wide RNAi screen identifies multiple synthetic lethal interactions with the Ras oncogene

STRING 8--a global view on proteins and their functional interactions in 630 organisms

Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci.

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1109-1121

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10.1101/GR.118992.110

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7

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21

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Edward Marcotte

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2011-05-02T00:00:00Z

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51092755

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21536720

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genome-wide association study

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3129253

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