Inference of gene regulatory network with S-system and artificial Bee Colony 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.

書目詳細資料
主要作者:	Obayed Bin Mahfuz
其他作者:	Showkat, Dilruba
格式:	Thesis
語言:	English
出版:	BRAC University 2015
主題:	Computer science and engineering Gene regulatory network Inference S-system DNA microarray Artificial bee colony
在線閱讀:	http://hdl.handle.net/10361/4371

id	10361-4371
record_format	dspace
spelling	10361-43712022-01-26T10:13:17Z Inference of gene regulatory network with S-system and artificial Bee Colony algorithm Obayed Bin Mahfuz Showkat, Dilruba Department of Computer Science and Engineering, BRAC University Computer science and engineering Gene regulatory network Inference S-system DNA microarray Artificial bee colony This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2015. Cataloged from PDF version of thesis report. Includes bibliographical references (page 51-53). Gene Regulatory Networks are the basic functional unit in living organisms. Gene Regulatory Network mainly refers to the behavior of thousands of genes (inside the chromosome of cell) with other genes. Each gene has expression levels and interaction with other genes. These interactions and expression levels can be calculated from their amount and time duration of protein production. Due to the invention of DNA microarray in biotechnology, we are able to find gene expression levels from real genetic regulatory networks. Now it’s the time to find a reverse process to reach a satisfactory result that matches with those data derived from DNA microarray. If we can find those values that satisfy the result, then we can predict our gene behavior much early. Watching abnormal gene behavior, diseases can be found .Thus it can be a revolutionary step towards medicine and diagnosis sector. If we reach better accuracy then it will also help us to develop tissue and organs. That means, for chronic disease or any other problem if one’s heart cannot pump blood, then he can repair his heart by making a new heart developed from the muscle cells from any other organ of his body. Biological systems are very much complex in nature. And S-system model is a recent and popular class to model biological systems. Hence, I am using S-system class for modeling. Gene Regulatory Networks contain a large number of genes. And artificial bee colony is best suited for population based problems. Hence, I am proposing an inference algorithm of gene regulatory network on the framework of S-system class of ordinary differential equations (ODEs) and artificial bee colony algorithm. Obayed Bin Mahfuz B. Computer Science and Engineering 2015-09-03T06:30:34Z 2015-09-03T06:30:34Z 2015 2015-08 Thesis ID 12101103 http://hdl.handle.net/10361/4371 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 53 pages application/pdf BRAC University
institution	Brac University
collection	Institutional Repository
language	English
topic	Computer science and engineering Gene regulatory network Inference S-system DNA microarray Artificial bee colony
spellingShingle	Computer science and engineering Gene regulatory network Inference S-system DNA microarray Artificial bee colony Obayed Bin Mahfuz Inference of gene regulatory network with S-system and artificial Bee Colony 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.
author2	Showkat, Dilruba
author_facet	Showkat, Dilruba Obayed Bin Mahfuz
format	Thesis
author	Obayed Bin Mahfuz
author_sort	Obayed Bin Mahfuz
title	Inference of gene regulatory network with S-system and artificial Bee Colony algorithm
title_short	Inference of gene regulatory network with S-system and artificial Bee Colony algorithm
title_full	Inference of gene regulatory network with S-system and artificial Bee Colony algorithm
title_fullStr	Inference of gene regulatory network with S-system and artificial Bee Colony algorithm
title_full_unstemmed	Inference of gene regulatory network with S-system and artificial Bee Colony algorithm
title_sort	inference of gene regulatory network with s-system and artificial bee colony algorithm
publisher	BRAC University
publishDate	2015
url	http://hdl.handle.net/10361/4371
work_keys_str_mv	AT obayedbinmahfuz inferenceofgeneregulatorynetworkwithssystemandartificialbeecolonyalgorithm
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Inference of gene regulatory network with S-system and artificial Bee Colony algorithm

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