Abstract
Ortholog detection methods present a powerful approach for finding genes that participate in similar biological processes across different organisms, extending our understanding of interactions between genes across different pathways, and understanding the evolution of gene families. We exploit features derived from the alignment of protein-protein interaction networks to reconstruct KEGG orthologs for Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository for protein-protein interaction data using the decision tree, Naive-Bayes and Support Vector Machine classification algorithms. The performance of our classifiers in reconstructing KEGG orthologs is compared against a basic reciprocal BLAST hit approach. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit.
| Original language | English (US) |
|---|---|
| Title of host publication | 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009 |
| Pages | 48-53 |
| Number of pages | 6 |
| DOIs | |
| State | Published - Dec 1 2009 |
| Event | 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009 - Washington, D.C., United States Duration: Nov 1 2009 → Nov 4 2009 |
Other
| Other | 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009 |
|---|---|
| Country | United States |
| City | Washington, D.C. |
| Period | 11/1/09 → 11/4/09 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Software
- Biomedical Engineering
- Health Informatics
Cite this
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Detection of gene orthology based on protein-protein interaction networks. / Towfic, Fadi; Greenlee, M. Heather West; Honavar, Vasant.
2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009. 2009. p. 48-53 5341866.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Detection of gene orthology based on protein-protein interaction networks
AU - Towfic, Fadi
AU - Greenlee, M. Heather West
AU - Honavar, Vasant
PY - 2009/12/1
Y1 - 2009/12/1
N2 - Ortholog detection methods present a powerful approach for finding genes that participate in similar biological processes across different organisms, extending our understanding of interactions between genes across different pathways, and understanding the evolution of gene families. We exploit features derived from the alignment of protein-protein interaction networks to reconstruct KEGG orthologs for Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository for protein-protein interaction data using the decision tree, Naive-Bayes and Support Vector Machine classification algorithms. The performance of our classifiers in reconstructing KEGG orthologs is compared against a basic reciprocal BLAST hit approach. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit.
AB - Ortholog detection methods present a powerful approach for finding genes that participate in similar biological processes across different organisms, extending our understanding of interactions between genes across different pathways, and understanding the evolution of gene families. We exploit features derived from the alignment of protein-protein interaction networks to reconstruct KEGG orthologs for Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository for protein-protein interaction data using the decision tree, Naive-Bayes and Support Vector Machine classification algorithms. The performance of our classifiers in reconstructing KEGG orthologs is compared against a basic reciprocal BLAST hit approach. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit.
UR - http://www.scopus.com/inward/record.url?scp=74549116506&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=74549116506&partnerID=8YFLogxK
U2 - 10.1109/BIBM.2009.85
DO - 10.1109/BIBM.2009.85
M3 - Conference contribution
AN - SCOPUS:74549116506
SN - 9780769538853
SP - 48
EP - 53
BT - 2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009
ER -