DocumentCode :
2736073
Title :
Linking molecular function and biological process terms in the ontology for gene expression data analysis
Author :
DeJongh, Matthew ; Van Dort, Pamela ; Ramsay, Benjamin
Author_Institution :
Dept. of Comput. Sci., Hope Coll., Holland, MI, USA
Volume :
2
fYear :
2004
fDate :
1-5 Sept. 2004
Firstpage :
2984
Lastpage :
2986
Abstract :
The gene ontology (GO) contains three hierarchies that represent gene function based on categories of molecular function, biological process, and cellular component. However, additional knowledge about the mechanisms underlying gene function is buried in the GO term definitions and is not computationally accessible. We describe a process for adding new links to the GO between molecular function terms and the biological process terms that those molecular functions are involved in. These new links enable inference engines to reason about relationships between genes that have disparate molecular functions but participate in the same biological process. In particular, we demonstrate how these new links enable more effective automated analysis of gene expression data.
Keywords :
biochemistry; biology computing; cellular biophysics; genetics; knowledge representation; learning (artificial intelligence); molecular biophysics; biological process; cellular component; gene expression data analysis; gene ontology; knowledge representation; machine learning; molecular function; Biochemistry; Biological processes; Computer science; Data analysis; Degradation; Electric breakdown; Gene expression; Joining processes; Ontologies; Radio access networks; Gene Expression Analysis; Gene Ontology; Knowledge Representation; Machine Learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-8439-3
Type :
conf
DOI :
10.1109/IEMBS.2004.1403846
Filename :
1403846
Link To Document :
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