Yörükoğlu, Deniz and Bakış, Yasin and Sezerman, Uğur (2009) An entropy based heuristic model for predicting functional sub-type divisions of protein families. In: 11th Genetic and Evolutionary Computation Conference, GECCO 2009, Montreal, Québec, Canada
PDF (This is a RoMEO green publisher -- author can archive pre-print (ie pre-refereeing) and post-print (ie final draft post-refereeing))
GECCOdeniz.pdf
Download (263kB)
GECCOdeniz.pdf
Download (263kB)
Official URL: http://doi.acm.org/10.1145/1570256.1570296
Abstract
Multiple sequence alignments of protein families are often used for locating residues that are widely apart in the sequence, which are considered as influential for determining functional specificity of proteins towards various substrates, ligands, DNA and other proteins. In this paper, we propose an entropy-score based heuristic algorithm model for predicting functional sub-family divisions of protein families, given the multiple sequence alignment of the protein family as input without any functional sub-type or key site
information given for any protein sequence. Two of the experimented test-cases are reported in this paper. First test-case is Nucleotidyl Cyclase protein family consisting of guanalyate and adenylate cyclases. And the second test-case is a dataset of proteins taken from six superfamilies in Structure-Function Linkage Database (SFLD). Results from these test-cases are reported in terms of confirmed sub-type divisions with phylogeny relations from former studies in the literature.
Item Type: | Papers in Conference Proceedings |
---|---|
Uncontrolled Keywords: | Protein Function, Classification, Multiple Sequence Alignment |
Subjects: | Q Science > Q Science (General) |
Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Biological Sciences & Bio Eng. Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng. |
Depositing User: | Uğur Sezerman |
Date Deposited: | 04 Dec 2009 09:38 |
Last Modified: | 26 Apr 2022 08:54 |
URI: | https://research.sabanciuniv.edu/id/eprint/13242 |