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19th International Conference on Scientific and Statistical Database Management (SSDBM 2007)
Gene Ontology-Based Annotation Analysis and Categorization of Metabolic Pathways
Banff, Alberta, Canada
July 09-July 11
ISBN: 0-7695-2868-6
ASCII Text
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Ali Cakmak, Mustafa Kirac, Marc R. Reynolds, Zehra M. Ozsoyoglu, Gultekin Ozsoyoglu, "Gene Ontology-Based Annotation Analysis and Categorization of Metabolic Pathways," Scientific and Statistical Database Management, International Conference on, pp. 33, 19th International Conference on Scientific and Statistical Database Management (SSDBM 2007), 2007.
 
 
BibTex
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@article{ 10.1109/SSDBM.2007.35,
author = {Ali Cakmak and Mustafa Kirac and Marc R. Reynolds and Zehra M. Ozsoyoglu and Gultekin Ozsoyoglu},
title = {Gene Ontology-Based Annotation Analysis and Categorization of Metabolic Pathways},
journal ={Scientific and Statistical Database Management, International Conference on},
volume = {0},
year = {2007},
issn = {1551-6393},
pages = {33},
doi = {http://doi.ieeecomputersociety.org/10.1109/SSDBM.2007.35},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Scientific and Statistical Database Management, International Conference on
TI - Gene Ontology-Based Annotation Analysis and Categorization of Metabolic Pathways
SN - 1551-6393
SP
EP
A1 - Ali Cakmak,
A1 - Mustafa Kirac,
A1 - Marc R. Reynolds,
A1 - Zehra M. Ozsoyoglu,
A1 - Gultekin Ozsoyoglu,
PY - 2007
KW - null
VL - 0
JA - Scientific and Statistical Database Management, International Conference on
ER -
 
Ali Cakmak, Case Western Reserve University, USA
Mustafa Kirac, Case Western Reserve University, USA
Marc R. Reynolds, Case Western Reserve University, USA
Zehra M. Ozsoyoglu, Case Western Reserve University, USA
Gultekin Ozsoyoglu, Case Western Reserve University, USA
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.

Citation:
Ali Cakmak, Mustafa Kirac, Marc R. Reynolds, Zehra M. Ozsoyoglu, Gultekin Ozsoyoglu, "Gene Ontology-Based Annotation Analysis and Categorization of Metabolic Pathways," ssdbm, pp.33, 19th International Conference on Scientific and Statistical Database Management (SSDBM 2007), 2007
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