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Geptop 2.0: An Updated, More Precise, and Faster Geptop Server for Identification of Prokaryotic Essential Genes
Geptop has performed effectively in the identification of prokaryotic essential genes since its first release in 2013. It estimates gene essentiality for prokaryotes based on orthology and phylogeny. Genome-scale essentiality data of more prokaryotic species are available, and the information has be...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6558110/ https://www.ncbi.nlm.nih.gov/pubmed/31214154 http://dx.doi.org/10.3389/fmicb.2019.01236 |
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author | Wen, Qing-Feng Liu, Shuo Dong, Chuan Guo, Hai-Xia Gao, Yi-Zhou Guo, Feng-Biao |
author_facet | Wen, Qing-Feng Liu, Shuo Dong, Chuan Guo, Hai-Xia Gao, Yi-Zhou Guo, Feng-Biao |
author_sort | Wen, Qing-Feng |
collection | PubMed |
description | Geptop has performed effectively in the identification of prokaryotic essential genes since its first release in 2013. It estimates gene essentiality for prokaryotes based on orthology and phylogeny. Genome-scale essentiality data of more prokaryotic species are available, and the information has been collected into public essential gene repositories such as DEG and OGEE. A faster and more accurate toolkit is needed to meet the increasing prokaryotic genome data. We updated Geptop by supplementing more validated essentiality data into reference set (from 19 to 37 species), and introducing multi-process technology to accelerate the computing speed. Compared with Geptop 1.0 and other gene essentiality prediction models, Geptop 2.0 can generate more stable predictions and finish the computation in a shorter time. The software is available both as an online server and a downloadable standalone application. We hope that the improved Geptop 2.0 will facilitate researches in gene essentiality and the development of novel antibacterial drugs. The gene essentiality prediction tool is available at http://cefg.uestc.cn/geptop. |
format | Online Article Text |
id | pubmed-6558110 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-65581102019-06-18 Geptop 2.0: An Updated, More Precise, and Faster Geptop Server for Identification of Prokaryotic Essential Genes Wen, Qing-Feng Liu, Shuo Dong, Chuan Guo, Hai-Xia Gao, Yi-Zhou Guo, Feng-Biao Front Microbiol Microbiology Geptop has performed effectively in the identification of prokaryotic essential genes since its first release in 2013. It estimates gene essentiality for prokaryotes based on orthology and phylogeny. Genome-scale essentiality data of more prokaryotic species are available, and the information has been collected into public essential gene repositories such as DEG and OGEE. A faster and more accurate toolkit is needed to meet the increasing prokaryotic genome data. We updated Geptop by supplementing more validated essentiality data into reference set (from 19 to 37 species), and introducing multi-process technology to accelerate the computing speed. Compared with Geptop 1.0 and other gene essentiality prediction models, Geptop 2.0 can generate more stable predictions and finish the computation in a shorter time. The software is available both as an online server and a downloadable standalone application. We hope that the improved Geptop 2.0 will facilitate researches in gene essentiality and the development of novel antibacterial drugs. The gene essentiality prediction tool is available at http://cefg.uestc.cn/geptop. Frontiers Media S.A. 2019-06-04 /pmc/articles/PMC6558110/ /pubmed/31214154 http://dx.doi.org/10.3389/fmicb.2019.01236 Text en Copyright © 2019 Wen, Liu, Dong, Guo, Gao and Guo. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Wen, Qing-Feng Liu, Shuo Dong, Chuan Guo, Hai-Xia Gao, Yi-Zhou Guo, Feng-Biao Geptop 2.0: An Updated, More Precise, and Faster Geptop Server for Identification of Prokaryotic Essential Genes |
title | Geptop 2.0: An Updated, More Precise, and Faster Geptop Server for Identification of Prokaryotic Essential Genes |
title_full | Geptop 2.0: An Updated, More Precise, and Faster Geptop Server for Identification of Prokaryotic Essential Genes |
title_fullStr | Geptop 2.0: An Updated, More Precise, and Faster Geptop Server for Identification of Prokaryotic Essential Genes |
title_full_unstemmed | Geptop 2.0: An Updated, More Precise, and Faster Geptop Server for Identification of Prokaryotic Essential Genes |
title_short | Geptop 2.0: An Updated, More Precise, and Faster Geptop Server for Identification of Prokaryotic Essential Genes |
title_sort | geptop 2.0: an updated, more precise, and faster geptop server for identification of prokaryotic essential genes |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6558110/ https://www.ncbi.nlm.nih.gov/pubmed/31214154 http://dx.doi.org/10.3389/fmicb.2019.01236 |
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