Abstract
The available number of protein sequences rapidly increased with the development of new sequencing techniques. This in turn led to an urgent need for the development of new computational methods utilizing these data for the solution of different biological problems. One of these problems is the comparison of protein sequences from different species to reveal their evolutional relationship. Recently, several alignment-free methods proposed for this purpose. Here in this study, we also proposed an alignment-free method for the same purpose. Different from the existing methods, the proposed method not only allows for a pairwise comparison of two protein sequences, but also it allows for a bulk comparison of multiple protein sequences simultaneously. Computational results performed on gold-standard datasets showed that, bulk comparison of multiple sequences is much faster than its pairwise counterpart and the proposed method achieves a performance which is quite competitive with the state-of-the-art alignment-based method, ClustalW.0000-0003-4810-1970
Highlights
DEVELOPMENT OF next-generation sequencing technologies led to a dramatic increase in the number of available deoxyribonucleic acid (DNA) and protein sequences
The second dataset consists of thirty-five Coronavirus Spike Proteins which were derived from the NCBI
This paper presented a new method for the similarity analysis of proteins from different species
Summary
DEVELOPMENT OF next-generation sequencing technologies led to a dramatic increase in the number of available DNA and protein sequences. It is quite crucial to effectively extract the biological information provided with this huge number of sequences which has given rise to new research challenges in computational biology and bioinformatics. Similarity analysis of protein sequences from different species is one of these research challenges. With the development of new tools for protein sequence similarity analysis, scientist will be able to elucidate the function of unknown proteins which may shed light on identification of potential drug targets and to gain insights on underlying molecular mechanisms of diseases [1]. BERAT DOĞAN, is with Department of Biomedical Engineering, Inonu https://orcid.org/0000-0003-4810-1970. Manuscript received March 16, 2019; accepted Sep 23, 2019.
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