dc.contributor.advisor | Ashraf, Faisal Bin | |
dc.contributor.author | Zaman, Shurid Shahriar | |
dc.contributor.author | Kabir, Tahseen Tayeb | |
dc.contributor.author | Islam, Md. Al-Junaed | |
dc.contributor.author | Alam, Syed Md. Shamsul | |
dc.date.accessioned | 2024-11-21T06:29:43Z | |
dc.date.available | 2024-11-21T06:29:43Z | |
dc.date.copyright | ©2021 | |
dc.date.issued | 2021-01 | |
dc.identifier.other | ID 17101087 | |
dc.identifier.other | ID 17101417 | |
dc.identifier.other | ID 17101438 | |
dc.identifier.other | ID 17301133 | |
dc.identifier.uri | http://hdl.handle.net/10361/24811 | |
dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. | en_US |
dc.description | Catalogued from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages 40-42). | |
dc.description.abstract | Finding patterns of the short sequences in DNA, RNA protein sequence has immense
biological signi cance. The characterization and recognition of motifs is therefore
an important method for a more in-depth understanding of genes or proteins in their
structure, function and relations of evolution. This is one of the classical problems in
the eld of computational biology and which is an NP Hard problem. In this paper,
we have proposed an evolutionary approach to get the motifs from DNA sequence
by searching candidate motifs using heuristic way from the data. We have included
various mutation techniques in an evolutionary approach and found an e cient way
to calculate the tness of our candidate motifs. We have evaluated the tness of
found motifs from our approach with benchmark data sets. Our method performs
better results in terms of accuracy and speci city. | en_US |
dc.description.statementofresponsibility | Shurid Shahriar Zaman | |
dc.description.statementofresponsibility | Tahseen Tayeb Kabir | |
dc.description.statementofresponsibility | Md. Al-Junaed Islam | |
dc.description.statementofresponsibility | Syed Md. Shamsul Alam | |
dc.format.extent | 85 pages | |
dc.language.iso | en | en_US |
dc.publisher | Brac University | en_US |
dc.rights | Brac University theses 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. | |
dc.subject | Bioinformatics | en_US |
dc.subject | Motifs recognition | en_US |
dc.subject | DNA sequence | en_US |
dc.subject | RNA protein sequence | en_US |
dc.subject | Heuristic approach | en_US |
dc.subject.lcsh | Bioinformatics--Mathematical models. | |
dc.subject.lcsh | Pattern recognition. | |
dc.subject.lcsh | Computational biology. | |
dc.subject.lcsh | Nucleotide sequence. | |
dc.subject.lcsh | Molecular biology--Computer simulation. | |
dc.title | Finding motifs from DNA sequence using heuristic approach | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, Brac University | |
dc.description.degree | B.Sc. in Computer Science and Engineering | |