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Exploiting ontology graph for predicting sparsely annotated gene function
- Source :
- Bioinformatics, Oxford University Press
- Publication Year :
- 2015
-
Abstract
- Motivation: Systematically predicting gene (or protein) function based on molecular interaction networks has become an important tool in refining and enhancing the existing annotation catalogs, such as the Gene Ontology (GO) database. However, functional labels with only a few (<br />National Institute of General Medical Sciences (U.S.) (Grant 1U54GM114838)
- Subjects :
- Statistics and Probability
Saccharomyces cerevisiae Proteins
Computer science
Gene regulatory network
Ismb/Eccb 2015 Proceedings Papers Committee July 10 to July 14, 2015, Dublin, Ireland
Overfitting
Machine learning
computer.software_genre
Biochemistry
Mice
Animals
Humans
Gene Regulatory Networks
Critical Assessment of Function Annotation
Molecular Biology
Gene
Data
business.industry
Computational Biology
Proteins
Molecular Sequence Annotation
Function (mathematics)
Yeast
Computer Science Applications
Computational Mathematics
ComputingMethodologies_PATTERNRECOGNITION
Gene Ontology
Computational Theory and Mathematics
Vocabulary, Controlled
Artificial intelligence
Data mining
business
computer
Algorithms
Subjects
Details
- ISSN :
- 13674811
- Volume :
- 31
- Issue :
- 12
- Database :
- OpenAIRE
- Journal :
- Bioinformatics (Oxford, England)
- Accession number :
- edsair.doi.dedup.....4a4e0289146b202767e85254fa43e4b1