A new method to measure the semantic similarity of GO terms.
about
An efficient weighted graph strategy to identify differentiation associated genes in embryonic stem cellsSemantic similarity in biomedical ontologiesLinking human diseases to animal models using ontology-based phenotype annotationMining phenotypes for gene function predictionIntelliGO: a new vector-based semantic similarity measure including annotation originCOFACTOR: an accurate comparative algorithm for structure-based protein function annotationDefining functional distances over gene ontologyFundamentals of protein interaction network mappingMining protein interactomes to improve their reliability and support the advancement of network medicineFunctional coherence metrics in protein familiesThe Longissimus and Semimembranosus muscles display marked differences in their gene expression profiles in pigA network of cancer genes with co-occurring and anti-co-occurring mutationsA second-generation protein-protein interaction network of Helicobacter pyloriBenchmarking human protein complexes to investigate drug-related systems and evaluate predicted protein complexesSemFunSim: a new method for measuring disease similarity by integrating semantic and gene functional associationEight paths of ERK1/2 signalling pathway regulating hepatocyte proliferation in rat liver regenerationKnowledge transfer via classification rules using functional mapping for integrative modeling of gene expression dataIntegrating human omics data to prioritize candidate genesFrom ontology to semantic similarity: calculation of ontology-based semantic similarityBioinformatics for personal genome interpretationFinding new genes for non-syndromic hearing loss through an in silico prioritization studyFrom disease ontology to disease-ontology lite: statistical methods to adapt a general-purpose ontology for the test of gene-ontology associationsDomain-mediated protein interaction prediction: From genome to network.A method for supporting retrieval of articles on protein structure analysis considering users' intention.Gene-disease relationship discovery based on model-driven data integration and database view definitionAutomatic, context-specific generation of Gene Ontology slims.Literature aided determination of data quality and statistical significance threshold for gene expression studies.Identifying protein complexes from heterogeneous biological data.Inferring gene networks from discrete expression data.M-Finder: Uncovering functionally associated proteins from interactome data integrated with GO annotations.Stratification of gene coexpression patterns and GO function mining for a RNA-Seq data series.Information content-based Gene Ontology functional similarity measures: which one to use for a given biological data type?Revealing and avoiding bias in semantic similarity scores for protein pairs.Assessing the functional coherence of gene sets with metrics based on the Gene Ontology graphA computational method for drug repositioning using publicly available gene expression data.Missing value imputation for microRNA expression data by using a GO-based similarity measure.Computational prediction of virus-human protein-protein interactions using embedding kernelized heterogeneous data.Quality assessment of protein model-structures based on structural and functional similarities.The duplicated genes database: identification and functional annotation of co-localised duplicated genes across genomesFusing literature and full network data improves disease similarity computation.
P2860
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P2860
A new method to measure the semantic similarity of GO terms.
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
2007年论文
@zh
2007年论文
@zh-cn
name
A new method to measure the semantic similarity of GO terms.
@en
type
label
A new method to measure the semantic similarity of GO terms.
@en
prefLabel
A new method to measure the semantic similarity of GO terms.
@en
P2093
P356
P1433
P1476
A new method to measure the semantic similarity of GO terms.
@en
P2093
Chin-Fu Chen
James Z Wang
Philip S Yu
Rapeeporn Payattakool
Zhidian Du
P304
P356
10.1093/BIOINFORMATICS/BTM087
P407
P577
2007-03-07T00:00:00Z