Solving multiple sequence alignment problems using various evolutionary algorithm

This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2015.

Bibliographic Details
Main Author:	Nazifa, Farah
Format:	Thesis
Language:	English
Published:	BRAC University 2015
Subjects:	Computer science and engineering Algorithm
Online Access:	http://hdl.handle.net/10361/4176

id	10361-4176
record_format	dspace
spelling	10361-41762022-01-26T10:19:58Z Solving multiple sequence alignment problems using various evolutionary algorithm Nazifa, Farah Computer science and engineering Algorithm This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2015. Bioinformatics is an art and science conceptualized with the use of computational biology. This review paints a broader picture of bioinformatics, on how the sequences of DNA, RNA are organized in the right possible alignment with minimal gap between the sequences. The roles of bioinformatics are highlighted at multiple points along the path from high-tech data generation to biological discovery. Sequence Alignment is used to find the areas of sequence similarity that could point to the structure of an evolutionary ancestor or provide information about the evolutionary history of the sequences. Multiple Sequence Alignment is a way of arranging the sequences of DNA and RNA to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. The work will involve study of multiple algorithms, Genetic Algorithm, Artificial Bee Colony Algorithm and Hybrid Algorithm. The proposed algorithms are implemented for solving the problem, Multiple Sequence Alignment. Result based on fitness against number of iterations graphical representation will show the best algorithm for this particular problem. However, results, similarities, differences efficiency of the implementations on these algorithms will be compared. 2015-06-01T10:08:58Z 2015-06-01T10:08:58Z 2015-05 Thesis ID 10201032 http://hdl.handle.net/10361/4176 en application/pdf BRAC University
institution	Brac University
collection	Institutional Repository
language	English
topic	Computer science and engineering Algorithm
spellingShingle	Computer science and engineering Algorithm Nazifa, Farah Solving multiple sequence alignment problems using various evolutionary algorithm
description	This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2015.
format	Thesis
author	Nazifa, Farah
author_facet	Nazifa, Farah
author_sort	Nazifa, Farah
title	Solving multiple sequence alignment problems using various evolutionary algorithm
title_short	Solving multiple sequence alignment problems using various evolutionary algorithm
title_full	Solving multiple sequence alignment problems using various evolutionary algorithm
title_fullStr	Solving multiple sequence alignment problems using various evolutionary algorithm
title_full_unstemmed	Solving multiple sequence alignment problems using various evolutionary algorithm
title_sort	solving multiple sequence alignment problems using various evolutionary algorithm
publisher	BRAC University
publishDate	2015
url	http://hdl.handle.net/10361/4176
work_keys_str_mv	AT nazifafarah solvingmultiplesequencealignmentproblemsusingvariousevolutionaryalgorithm
_version_	1814309085033529344

Solving multiple sequence alignment problems using various evolutionary algorithm

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