Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Hashim, Fatma A., Mabrouk, Mai S., Al-Atabany, Walid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Avicenna Research Institute 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6490410/
https://www.ncbi.nlm.nih.gov/pubmed/31057715
_version_ 1783414880384057344
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