Biological Sequence Alignment - A Review
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 12
Abstract
Bioinformatics is an emerging interdisciplinary research area that deals with the computational management and analysis of biological information. Genomics is the most important domain in bioinformatics which compares genomic features like DNA sequences, genes, regulatory sequences, or other genomic structural components etc. of different organisms. Computers are used to gather, store, analyze and integrate biological and genetic information which can then be applied to gene-based drug discovery and development. Scientists may require weeks or months if they use their own workstations since biological big data is generated by several different bioinformatics/biological/biomedical experiments and it can be presented as structured or unstructured data. Each cell in the body contains a whole genome, yet the data packed into a few DNA molecules could fill a hard drive. Biological big data is now reaching the size of Terabytes, Petabytes and exa bytes and the different modes of representation adds complexity. It introduces many challenges such as handling of complex information; integration of heterogeneous resources; analysis on big data. Advanced methods to handle the volume of data and speed of analysis scientists may require weeks or months if they use their own workstations. Sequence alignment is a standard technique in bioinformatics for visualizing the relationships between residues in a collection of evolutionarily or structurally related proteins. In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity which may be a consequence of functional, structural, or evolutionary relationships between the sequences and are used to infer biological information. Since the sequence data bases are big databases, the existing techniques and algorithms have several computational challenges. A review of the major sequence alignment algorithms are discussed in this paper.
Authors and Affiliations
Kala Karun, Dancy Kurian, Sheeja Y. S.
Keywords
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- DOI 10.9790/9622-0712011823.
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