Representing Protein Sequence with Low Number of Dimensions

Nazar Zaki, Safaai Deris, Nazar Mustafa Ahmed

Research output: Contribution to journalArticlepeer-review


This study introduces a simple method based on representing protein sequence by fix dimensions of the length three. We present hidden Markov model combining scores method. Three scoring algorithms are combined to represent protein sequence of amino acids for better remote homology detection. We tested the method on the SCOP version 1.37 dataset. The results show that, with such a simple representation, we are able to achieve superior performance to previously presented protein homology detection methods while achieving better computational efficiency
Original languageEnglish
Pages (from-to)795-800
JournalJournal of Biological Sciences
Publication statusPublished - 2005


Dive into the research topics of 'Representing Protein Sequence with Low Number of Dimensions'. Together they form a unique fingerprint.

Cite this