Cargando…

Visualization of DNA Sequence Features Based on Cellular Automata

Visualization of special patterns in biological sequences can assist revealing important roles in gene regulation and other basic molecular activities of the sequence. The visualization method needs to highlight interesting sequence patterns while suppressing trivial aspects. A biology sequences vis...

Descripción completa

Detalles Bibliográficos
Autores principales: Huang, Qingnan, Wang, Xuanqi, Li, Huili, He, Feng, Wu, Xiaoming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120233/
http://dx.doi.org/10.1007/978-3-642-25778-0_12
_version_ 1783514930652119040
author Huang, Qingnan
Wang, Xuanqi
Li, Huili
He, Feng
Wu, Xiaoming
author_facet Huang, Qingnan
Wang, Xuanqi
Li, Huili
He, Feng
Wu, Xiaoming
author_sort Huang, Qingnan
collection PubMed
description Visualization of special patterns in biological sequences can assist revealing important roles in gene regulation and other basic molecular activities of the sequence. The visualization method needs to highlight interesting sequence patterns while suppressing trivial aspects. A biology sequences visualization scheme based on cellular automata is developed in this study. Features such as alleles of a DNA sequence were extracted and mapped into a grid in a two-dimensional plane, creating an initial pattern. Then, two-dimensional cellular automata were iteratively executed according to predefined rules and turned the initial pattern into a two-dimensional pattern, forming the fingerprint of the sequence. This fingerprint can be served as a representation of the sequence and can be used to make sequences comparing.
format Online
Article
Text
id pubmed-7120233
institution National Center for Biotechnology Information
language English
publishDate 2012
record_format MEDLINE/PubMed
spelling pubmed-71202332020-04-06 Visualization of DNA Sequence Features Based on Cellular Automata Huang, Qingnan Wang, Xuanqi Li, Huili He, Feng Wu, Xiaoming Recent Advances in Computer Science and Information Engineering Article Visualization of special patterns in biological sequences can assist revealing important roles in gene regulation and other basic molecular activities of the sequence. The visualization method needs to highlight interesting sequence patterns while suppressing trivial aspects. A biology sequences visualization scheme based on cellular automata is developed in this study. Features such as alleles of a DNA sequence were extracted and mapped into a grid in a two-dimensional plane, creating an initial pattern. Then, two-dimensional cellular automata were iteratively executed according to predefined rules and turned the initial pattern into a two-dimensional pattern, forming the fingerprint of the sequence. This fingerprint can be served as a representation of the sequence and can be used to make sequences comparing. 2012-02-05 /pmc/articles/PMC7120233/ http://dx.doi.org/10.1007/978-3-642-25778-0_12 Text en © Springer-Verlag GmbH Berlin Heidelberg 2012 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Huang, Qingnan
Wang, Xuanqi
Li, Huili
He, Feng
Wu, Xiaoming
Visualization of DNA Sequence Features Based on Cellular Automata
title Visualization of DNA Sequence Features Based on Cellular Automata
title_full Visualization of DNA Sequence Features Based on Cellular Automata
title_fullStr Visualization of DNA Sequence Features Based on Cellular Automata
title_full_unstemmed Visualization of DNA Sequence Features Based on Cellular Automata
title_short Visualization of DNA Sequence Features Based on Cellular Automata
title_sort visualization of dna sequence features based on cellular automata
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120233/
http://dx.doi.org/10.1007/978-3-642-25778-0_12
work_keys_str_mv AT huangqingnan visualizationofdnasequencefeaturesbasedoncellularautomata
AT wangxuanqi visualizationofdnasequencefeaturesbasedoncellularautomata
AT lihuili visualizationofdnasequencefeaturesbasedoncellularautomata
AT hefeng visualizationofdnasequencefeaturesbasedoncellularautomata
AT wuxiaoming visualizationofdnasequencefeaturesbasedoncellularautomata