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BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters
Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists; accordingly, its application in biological research has been limited. In order to popularize this technology in the field o...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5712467/ https://www.ncbi.nlm.nih.gov/pubmed/29204317 http://dx.doi.org/10.7717/peerj.3948 |
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author | Cheng, Gong Lu, Quan Ma, Ling Zhang, Guocai Xu, Liang Zhou, Zongshan |
author_facet | Cheng, Gong Lu, Quan Ma, Ling Zhang, Guocai Xu, Liang Zhou, Zongshan |
author_sort | Cheng, Gong |
collection | PubMed |
description | Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists; accordingly, its application in biological research has been limited. In order to popularize this technology in the field of bioinformatics and to promote the use of publicly available bioinformatics tools, such as Dockerfiles and Images from communities, government sources, and private owners in the Docker Hub Registry and other Docker-based resources, we introduce here a complete and accurate bioinformatics workflow based on Docker. The present workflow enables analysis and visualization of pan-genomes and biosynthetic gene clusters of bacteria. This provides a new solution for bioinformatics mining of big data from various publicly available biological databases. The present step-by-step guide creates an integrative workflow through a Dockerfile to allow researchers to build their own Image and run Container easily. |
format | Online Article Text |
id | pubmed-5712467 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57124672017-12-04 BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters Cheng, Gong Lu, Quan Ma, Ling Zhang, Guocai Xu, Liang Zhou, Zongshan PeerJ Bioinformatics Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists; accordingly, its application in biological research has been limited. In order to popularize this technology in the field of bioinformatics and to promote the use of publicly available bioinformatics tools, such as Dockerfiles and Images from communities, government sources, and private owners in the Docker Hub Registry and other Docker-based resources, we introduce here a complete and accurate bioinformatics workflow based on Docker. The present workflow enables analysis and visualization of pan-genomes and biosynthetic gene clusters of bacteria. This provides a new solution for bioinformatics mining of big data from various publicly available biological databases. The present step-by-step guide creates an integrative workflow through a Dockerfile to allow researchers to build their own Image and run Container easily. PeerJ Inc. 2017-11-30 /pmc/articles/PMC5712467/ /pubmed/29204317 http://dx.doi.org/10.7717/peerj.3948 Text en © 2017 Cheng et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Cheng, Gong Lu, Quan Ma, Ling Zhang, Guocai Xu, Liang Zhou, Zongshan BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters |
title | BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters |
title_full | BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters |
title_fullStr | BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters |
title_full_unstemmed | BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters |
title_short | BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters |
title_sort | bgdmdocker: a docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5712467/ https://www.ncbi.nlm.nih.gov/pubmed/29204317 http://dx.doi.org/10.7717/peerj.3948 |
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