In silico gene prioritization by integrating multiple data sources
about
A multi-platform draft de novo genome assembly and comparative analysis for the Scarlet Macaw (Ara macao)Identifying disease genes by integrating multiple data sourcesA fast and high performance multiple data integration algorithm for identifying human disease genes.Mining breast cancer genes with a network based noise-tolerant approachData sources for in vivo molecular profiling of human phenotypes.An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.Drug repositioning by integrating target information through a heterogeneous network model.Prioritization of candidate genes for attention deficit hyperactivity disorder by computational analysis of multiple data sources.GroupRank: rank candidate genes in PPI network by differentially expressed gene groups.In silico molecular cytogenetics: a bioinformatic approach to prioritization of candidate genes and copy number variations for basic and clinical genome research.An algorithm for network-based gene prioritization that encodes knowledge both in nodes and in links.Harnessing gene expression networks to prioritize candidate epileptic encephalopathy genes.OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.A new method to improve network topological similarity search: applied to fold recognitionGeneTIER: prioritization of candidate disease genes using tissue-specific gene expression profilesImportance of different types of prior knowledge in selecting genome-wide findings for follow-up.Recent approaches to the prioritization of candidate disease genes.Candidate gene prioritization.Identifying new targets in leukemogenesis using computational approaches.Prioritization of candidate genes for periodontitis using multiple computational tools.Drug target predictions based on heterogeneous graph inference.Scuba: scalable kernel-based gene prioritization.Multidimensional knowledge-based framework is an essential step in the categorization of gene sets in complex disorders.Mice lacking the Parkinson's related GPR37/PAEL receptor show non-motor behavioral phenotypes: age and gender effect.pBRIT: Gene Prioritization by Correlating Functional and Phenotypic Annotations Through Integrative Data Fusion.Disease gene identification by using graph kernels and Markov random fields.Prioritization of candidate disease genes by enlarging the seed set and fusing information of the network topology and gene expression.
P2860
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P2860
In silico gene prioritization by integrating multiple data sources
description
2011 nî lūn-bûn
@nan
2011 թուականին հրատարակուած գիտական յօդուած
@hyw
2011 թվականին 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
In silico gene prioritization by integrating multiple data sources
@ast
In silico gene prioritization by integrating multiple data sources
@en
In silico gene prioritization by integrating multiple data sources
@en-gb
In silico gene prioritization by integrating multiple data sources
@nl
type
label
In silico gene prioritization by integrating multiple data sources
@ast
In silico gene prioritization by integrating multiple data sources
@en
In silico gene prioritization by integrating multiple data sources
@en-gb
In silico gene prioritization by integrating multiple data sources
@nl
prefLabel
In silico gene prioritization by integrating multiple data sources
@ast
In silico gene prioritization by integrating multiple data sources
@en
In silico gene prioritization by integrating multiple data sources
@en-gb
In silico gene prioritization by integrating multiple data sources
@nl
P2093
P2860
P1433
P1476
In silico gene prioritization by integrating multiple data sources
@en
P2093
Robert C Elston
Robert Shields
Sumit K Chanda
Yingyao Zhou
Yixuan Chen
P2860
P304
P356
10.1371/JOURNAL.PONE.0021137
P407
P577
2011-01-01T00:00:00Z