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Multiple sequence alignment using biological features classification
| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Besharati, A. Jalali, M. |
| Copyright Year | 2014 |
| Description | Author affiliation: Islamic Azad Univ., Mashhad, Iran (Jalali, M.) || Imam Reza Int. Univ., Mashhad, Iran (Besharati, A.) |
| 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. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 232178 |
| Page Count | 5 |
| File Format | |
| e-ISBN | 9781479980215 |
| DOI | 10.1109/ICTCK.2014.7033511 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-11-26 |
| Publisher Place | Iran |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Proteins Databases Multiple sequence alignment Clustering algorithms Scoring function Classification algorithms Reliability Clustering Bioinformatics |
| Content Type | Text |
| Resource Type | Article |
