An Extension to Local Network Alignment using Hidden Markov Models (HMMs)
Hakan Gündüz, İbrahim Süzer
2016
Abstract
Local alignment is done on biological networks to find common conserved substructures belonging to different organisms. Many algorithms such as PathBLAST (Kelley et al., 2003), Network-BLAST (Scott et al., 2006) are used to align networks locally and they are generally good at finding small sized common substructures. However, these algorithms have same failures about finding larger substructures because of complexity issues. To overcome these issues, Hidden Markov Models (HMMs) is used. The study done by (Qian and Yoon, 2009), uses HMMs to find optimal conserved paths in two biological networks where aligned paths have constant path length. In this paper, we aim to make an extension to the local network alignment procedure done in (Qian and Yoon, 2009) to find common substructures in varying length sizes between the biological networks. We again used same algorithm to find k-length exact matches from networks and we used them to find common substructures in two forms as sub-graphs and extended paths. These structures do not need to have the same number of nodes and should satisfy the predefined similarity threshold (s0). The other parameter is the length of exact paths (k) formed from biological networks and choosing a lower k value is faster but bigger values might be needed in order to balance the number of matching paths below s0.
References
- Döpmann, C. (2013). Survey on the graph alignment problem and a benchmark of suitable algorithms.
- Kanehisa, M. and Goto, S. (2000). KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Research, 28(1):27-30.
- Kelley, B. P., Sharan, R., Karp, R. M., Sittler, T., Root, D. E., Stockwell, B. R., and Ideker, T. (2003). Conserved pathways within bacteria and yeast as revealed by global protein network alignment. Proceedings of the National Academy of Sciences, 100(20):11394- 11399.
- Li, Z., Zhang, S., Wang, Y., Zhang, X.-S., and Chen, L. (2007). Alignment of molecular networks by integer quadratic programming. Bioinformatics, 23(13):1631-1639.
- Liao, C.-S., Lu, K., Baym, M., Singh, R., and Berger, B. (2009). Isorankn: spectral methods for global alignment of multiple protein networks. Bioinformatics, 25(12):i253-i258.
- Qian, X. and Yoon, B.-J. (2009). Effective identification of conserved pathways in biological networks using hidden markov models. PLoS One, 4(12):e8070.
- Scott, J., Ideker, T., Karp, R. M., and Sharan, R. (2006). Efficient algorithms for detecting signaling pathways in protein interaction networks. Journal of Computational Biology, 13(2):133-144.
- Shlomi, T., Segal, D., Ruppin, E., and Sharan, R. (2006). Qpath: a method for querying pathways in a proteinprotein interaction network. BMC bioinformatics, 7(1):199.
- Von Mering, C., Krause, R., Snel, B., Cornell, M., Oliver, S. G., Fields, S., and Bork, P. (2002). Comparative assessment of large-scale data sets of protein-protein interactions. Nature, 417(6887):399-403.
- Yang, Q. and Sze, S.-H. (2007). Path matching and graph matching in biological networks. Journal of Computational Biology, 14(1):56-67.
- Zaslavskiy, M., Bach, F., and Vert, J.-P. (2009). Global alignment of protein-protein interaction networks by graph matching methods. Bioinformatics, 25(12):i259-1267.
Paper Citation
in Harvard Style
Gündüz H. and Süzer İ. (2016). An Extension to Local Network Alignment using Hidden Markov Models (HMMs) . In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 253-257. DOI: 10.5220/0005742102530257
in Bibtex Style
@conference{bioinformatics16,
author={Hakan Gündüz and İbrahim Süzer},
title={An Extension to Local Network Alignment using Hidden Markov Models (HMMs)},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)},
year={2016},
pages={253-257},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005742102530257},
isbn={978-989-758-170-0},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)
TI - An Extension to Local Network Alignment using Hidden Markov Models (HMMs)
SN - 978-989-758-170-0
AU - Gündüz H.
AU - Süzer İ.
PY - 2016
SP - 253
EP - 257
DO - 10.5220/0005742102530257