Gene Ontology-Based Annotation Analysis and Categorization of Metabolic Pathways

Functional characterizations of pathways provide new opportunities in defining, understanding, and comparing existing biological pathways, and in helping discover new ones in different organisms. In this paper, we present and evaluate computational techniques for categorizing pathways, based upon th...

Full description

Saved in:
Bibliographic Details
Published in19th International Conference on Scientific and Statistical Database Management (SSDBM 2007) p. 33
Main Authors Cakmak, A., Kirac, M., Reynolds, M.R., Ozsoyoglu, Z.M., Ozsoyoglu, G.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2007
Subjects
Biochemistry
Bioinformatics
Biological processes
Biological system modeling
Genomics
Ontologies
Organisms
Performance evaluation
Statistical analysis
Visualization
Online AccessGet full text

Cover

More Information
Summary:Functional characterizations of pathways provide new opportunities in defining, understanding, and comparing existing biological pathways, and in helping discover new ones in different organisms. In this paper, we present and evaluate computational techniques for categorizing pathways, based upon the Gene Ontology (GO) annotations of enzymes within metabolic pathways. Our approach is to use the notion of functionality templates, GO-functional graphs of pathways. Pathway categorization is then achieved through learning models built on different characteristics of functionality templates. We have experimentally evaluated the accuracy of automated pathway categorization with respect to different learning models and their parameters. Using KEGG metabolic pathways, the pathway categorization tool reaches to 90% and higher accuracy.
ISSN:1551-6393
DOI:10.1109/SSDBM.2007.35