Biological Sequence Matching - Gill, Nivit;Singh, Shailendra
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Biological sequence alignment is one of the crucial tasks of computational biology, and provides base for other tasks of bioinformatics. It has been consistent effort of researchers to employ different techniques for sequence alignment so as to get better results. This book is an adaptation of the master s dissertation, which was a research initiative carried in the field of biological sequence alignment. The work was about two distinct approaches to sequence matching Boolean algebra and Fuzzy logic a two-valued logic and a multi-valued logic. Both the methods determine the similarity between…mehr

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Produktbeschreibung
Biological sequence alignment is one of the crucial tasks of computational biology, and provides base for other tasks of bioinformatics. It has been consistent effort of researchers to employ different techniques for sequence alignment so as to get better results. This book is an adaptation of the master s dissertation, which was a research initiative carried in the field of biological sequence alignment. The work was about two distinct approaches to sequence matching Boolean algebra and Fuzzy logic a two-valued logic and a multi-valued logic. Both the methods determine the similarity between the sequences by direct comparison method using the operations of Boolean algebra and Fuzzy logic respectively. Then on the basis of their degree of similarity, multiple DNA sequences are aligned progressively using dynamic programming to ensure optimal alignment. The methods are implemented in MATLAB® and tested on various sets of DNA sequences of different influenza A virus types taken from NCBI bank. Three different aspects of the discussed approaches have been assessed using different data sets.
Autorenporträt
Nivit Gill is a faculty member of Punjabi University Regional Centre, Mohali. She obtained her MCA degree from the Department of Computer Science, Punjabi University, Patiala and her ME degree from PEC University of Technology, Chandigarh. Her research areas include bioinformatics, networks and network security.