Combining Multisource Information Through Functional-Annotation-Based Weighting: Gene Function Prediction in Yeast

Motivation: One of the important goals of biological investigation is to predict the function of unclassified gene. Although there is a rich literature on multi data source integration for gene function prediction, there is hardly any similar work in the framework of data source weighting using func...

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Veröffentlicht in:	IEEE transactions on biomedical engineering Jg. 56; H. 2; S. 229 - 236
Hauptverfasser:	Sankar Ray $^{\ast}$, Shubhra, Bandyopadhyay, Sanghamitra, Pal, Sankar K.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.02.2009 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Annotations Bayesian methods Bioinformatics Biology computing Categories Cluster Analysis Clustering algorithms combinatorial optimization Computational Biology - methods Data sources Databases, Genetic Fungi Gene expression Gene Expression Profiling Genes Genes, Fungal Genomics Mathematical analysis Mathematical models Models, Genetic Oligonucleotide Array Sequence Analysis Ontologies phenotypic profile Protein Interaction Mapping protein sequence Proteins Reproducibility of Results Saccharomyces Saccharomyces cerevisiae - genetics Saccharomyces cerevisiae Proteins - chemistry Saccharomyces cerevisiae Proteins - genetics Saccharomyces cerevisiae Proteins - physiology Sequence Analysis, Protein transitive homology Weighting Yeast Yeasts
ISSN:	0018-9294, 1558-2531
Online-Zugang:	Volltext
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