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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2012
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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 |
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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 |