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Review of Different Sequence Motif Finding Algorithms
The DNA motif discovery is a primary step in many systems for studying gene function. Motif discovery plays a vital role in identification of Transcription Factor Binding Sites (TFBSs) that help in learning the mechanisms for regulation of gene expression. Over the past decades, different algorithms...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Avicenna Research Institute
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6490410/ https://www.ncbi.nlm.nih.gov/pubmed/31057715 |
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author | Hashim, Fatma A. Mabrouk, Mai S. Al-Atabany, Walid |
author_facet | Hashim, Fatma A. Mabrouk, Mai S. Al-Atabany, Walid |
author_sort | Hashim, Fatma A. |
collection | PubMed |
description | The DNA motif discovery is a primary step in many systems for studying gene function. Motif discovery plays a vital role in identification of Transcription Factor Binding Sites (TFBSs) that help in learning the mechanisms for regulation of gene expression. Over the past decades, different algorithms were used to design fast and accurate motif discovery tools. These algorithms are generally classified into consensus or probabilistic approaches that many of them are time-consuming and easily trapped in a local optimum. Nature-inspired algorithms and many of combinatorial algorithms are recently proposed to overcome these problems. This paper presents a general classification of motif discovery algorithms with new sub-categories that facilitate building a successful motif discovery algorithm. It also presents a summary of comparison between them. |
format | Online Article Text |
id | pubmed-6490410 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Avicenna Research Institute |
record_format | MEDLINE/PubMed |
spelling | pubmed-64904102019-05-03 Review of Different Sequence Motif Finding Algorithms Hashim, Fatma A. Mabrouk, Mai S. Al-Atabany, Walid Avicenna J Med Biotechnol Review Article The DNA motif discovery is a primary step in many systems for studying gene function. Motif discovery plays a vital role in identification of Transcription Factor Binding Sites (TFBSs) that help in learning the mechanisms for regulation of gene expression. Over the past decades, different algorithms were used to design fast and accurate motif discovery tools. These algorithms are generally classified into consensus or probabilistic approaches that many of them are time-consuming and easily trapped in a local optimum. Nature-inspired algorithms and many of combinatorial algorithms are recently proposed to overcome these problems. This paper presents a general classification of motif discovery algorithms with new sub-categories that facilitate building a successful motif discovery algorithm. It also presents a summary of comparison between them. Avicenna Research Institute 2019 /pmc/articles/PMC6490410/ /pubmed/31057715 Text en Copyright© 2019 Avicenna Research Institute http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Hashim, Fatma A. Mabrouk, Mai S. Al-Atabany, Walid Review of Different Sequence Motif Finding Algorithms |
title | Review of Different Sequence Motif Finding Algorithms |
title_full | Review of Different Sequence Motif Finding Algorithms |
title_fullStr | Review of Different Sequence Motif Finding Algorithms |
title_full_unstemmed | Review of Different Sequence Motif Finding Algorithms |
title_short | Review of Different Sequence Motif Finding Algorithms |
title_sort | review of different sequence motif finding algorithms |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6490410/ https://www.ncbi.nlm.nih.gov/pubmed/31057715 |
work_keys_str_mv | AT hashimfatmaa reviewofdifferentsequencemotiffindingalgorithms AT mabroukmais reviewofdifferentsequencemotiffindingalgorithms AT alatabanywalid reviewofdifferentsequencemotiffindingalgorithms |