Prediction of UTR5’, CDS AND UTR3’ Splice sites in an unknown DNA sequence
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014.
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10361-29002022-01-26T10:13:11Z Prediction of UTR5’, CDS AND UTR3’ Splice sites in an unknown DNA sequence Chaki, Dipankar Roushan, Tanvir Chowdhury, Md. Syeed Ali, Abu Mohammad Hammad Department of Computer Science and Engineering, BRAC University UTR5 UTR3 CDS splice sites Computer science and engineering Markov models Machine learning. This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014. Cataloged from PDF version of thesis report. Includes bibliographical references (page 51-53). The recent flood of data from genome sequences and functional genomics has given rise to a new field, bioinformatics, which combines elements of biology and computer science. In experimental molecular biology, bioinformatics techniques such as image and signal processing allow extraction of useful results from large amounts of raw data. In the field of genetics and genomics, it aids in sequencing and annotating genomes. Given a biological sequence, such as a Deoxyribonucleic acid (DNA) sequence, biologists would like to analyze what that sequence represents. A challenging and interesting problem in computational biology at the moment is finding genes in DNA sequences. With so many genomes being sequenced rapidly, it remains important to begin by identifying genes computationally. A DNA sequence consists of four nucleotide bases. There are two untranslated regions UTR5’ and UTR3’, which is not translated during the process of translation. The nucleotide base pair between UTR5’ and UTR3’ is known as the code section (CDS). Our goal is to find and develop a way to determine a likelihood value (using hidden Markov model), based on which the joining sections of these three regions can by identified in any given sequence. Dipankar Chaki Tanvir Roushan Md. Syeed Chowdhury B. Computer Science and Engineering 2014-01-29T06:06:57Z 2014-01-29T06:06:57Z 2014 2014-01 Thesis ID 09101017 ID 09201006 ID 09201014 http://hdl.handle.net/10361/2900 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. 54 pages application/pdf BRAC University BRAC University |
institution |
Brac University |
collection |
Institutional Repository |
language |
English |
topic |
UTR5 UTR3 CDS splice sites Computer science and engineering Markov models Machine learning. |
spellingShingle |
UTR5 UTR3 CDS splice sites Computer science and engineering Markov models Machine learning. Chaki, Dipankar Roushan, Tanvir Chowdhury, Md. Syeed Prediction of UTR5’, CDS AND UTR3’ Splice sites in an unknown DNA sequence |
description |
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014. |
author2 |
Ali, Abu Mohammad Hammad |
author_facet |
Ali, Abu Mohammad Hammad Chaki, Dipankar Roushan, Tanvir Chowdhury, Md. Syeed |
format |
Thesis |
author |
Chaki, Dipankar Roushan, Tanvir Chowdhury, Md. Syeed |
author_sort |
Chaki, Dipankar |
title |
Prediction of UTR5’, CDS AND UTR3’ Splice sites in an unknown DNA sequence |
title_short |
Prediction of UTR5’, CDS AND UTR3’ Splice sites in an unknown DNA sequence |
title_full |
Prediction of UTR5’, CDS AND UTR3’ Splice sites in an unknown DNA sequence |
title_fullStr |
Prediction of UTR5’, CDS AND UTR3’ Splice sites in an unknown DNA sequence |
title_full_unstemmed |
Prediction of UTR5’, CDS AND UTR3’ Splice sites in an unknown DNA sequence |
title_sort |
prediction of utr5’, cds and utr3’ splice sites in an unknown dna sequence |
publisher |
BRAC University |
publishDate |
2014 |
url |
http://hdl.handle.net/10361/2900 |
work_keys_str_mv |
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