DocumentCode :
260210
Title :
Multiple sequence alignment using biological features classification
Author :
Besharati, Arezoo ; Jalali, Mehrdad
Author_Institution :
Imam Reza Int. Univ., Mashhad, Iran
fYear :
2014
fDate :
26-27 Nov. 2014
Firstpage :
1
Lastpage :
5
Abstract :
Multiple biological sequences alignment like protein sequences or DNA/RNA in order to discover the functions, structures and evolutionary relationships among species and also discovering drugs is a fundamental study in bioinformatics. Unfortunately the multiple sequence alignment is a NP-complete problem and the reliability of the existing algorithms is not so high. The objective of our study was to improve multiple sequence alignment using biological features such as secondary structure of the sequences available in knowledge databases like SWISSPROT to achieve a more reliable alignment. We also provide a new method for grouping the similar sequences using biological features. The results of our tests on these databases indicate that the accuracy of the provided FCB MSA algorithm is much more than the existing alignment tools such as T-COFFEE and MAFFT.
Keywords :
DNA; RNA; bioinformatics; computational complexity; drugs; genetics; genomics; molecular biophysics; molecular configurations; optimisation; proteins; DNA/RNA; FCB MSA algorithm; MAFFT; NP-complete problem; SWISSPROT; T-COFFEE; bioinformatics; biological feature classification; drugs; evolutionary relationships; functions; multiple biological sequence alignment; multiple sequence alignment; protein sequences; secondary structure; structures; Bioinformatics; Classification algorithms; Clustering algorithms; Databases; Proteins; Reliability; Bioinformatics; Clustering; Multiple sequence alignment; Scoring function;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Technology, Communication and Knowledge (ICTCK), 2014 International Congress on
Conference_Location :
Mashhad
Type :
conf
DOI :
10.1109/ICTCK.2014.7033511
Filename :
7033511
Link To Document :
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