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EuGène-maize: a web site for maize gene prediction
Motivation:A large part of the maize B73 genome sequence is now available and emerging sequencing technologies will offer cheap and easy ways to sequence areas of interest from many other maize genotypes. One of the steps required to turn these sequences into valuable information is gene content pre...
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
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Oxford University Press
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2859131/ https://www.ncbi.nlm.nih.gov/pubmed/20400755 http://dx.doi.org/10.1093/bioinformatics/btq123 |
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author | Montalent, Pierre Joets, Johann |
author_facet | Montalent, Pierre Joets, Johann |
author_sort | Montalent, Pierre |
collection | PubMed |
description | Motivation:A large part of the maize B73 genome sequence is now available and emerging sequencing technologies will offer cheap and easy ways to sequence areas of interest from many other maize genotypes. One of the steps required to turn these sequences into valuable information is gene content prediction. To date, there is no publicly available gene predictor specifically trained for maize sequences. To this end, we have chosen to train the EuGène software that can combine several sources of evidence into a consolidated gene model prediction. Availability: http://genome.jouy.inra.fr/eugene/cgi-bin/eugene_form.pl Contact: joets@moulon.inra.fr Supplementary information:Supplementary data are available at Bioinformatics online. |
format | Text |
id | pubmed-2859131 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-28591312010-04-26 EuGène-maize: a web site for maize gene prediction Montalent, Pierre Joets, Johann Bioinformatics Applications Note Motivation:A large part of the maize B73 genome sequence is now available and emerging sequencing technologies will offer cheap and easy ways to sequence areas of interest from many other maize genotypes. One of the steps required to turn these sequences into valuable information is gene content prediction. To date, there is no publicly available gene predictor specifically trained for maize sequences. To this end, we have chosen to train the EuGène software that can combine several sources of evidence into a consolidated gene model prediction. Availability: http://genome.jouy.inra.fr/eugene/cgi-bin/eugene_form.pl Contact: joets@moulon.inra.fr Supplementary information:Supplementary data are available at Bioinformatics online. Oxford University Press 2010-05-01 2010-04-16 /pmc/articles/PMC2859131/ /pubmed/20400755 http://dx.doi.org/10.1093/bioinformatics/btq123 Text en © The Author(s) 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Montalent, Pierre Joets, Johann EuGène-maize: a web site for maize gene prediction |
title | EuGène-maize: a web site for maize gene prediction |
title_full | EuGène-maize: a web site for maize gene prediction |
title_fullStr | EuGène-maize: a web site for maize gene prediction |
title_full_unstemmed | EuGène-maize: a web site for maize gene prediction |
title_short | EuGène-maize: a web site for maize gene prediction |
title_sort | eugène-maize: a web site for maize gene prediction |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2859131/ https://www.ncbi.nlm.nih.gov/pubmed/20400755 http://dx.doi.org/10.1093/bioinformatics/btq123 |
work_keys_str_mv | AT montalentpierre eugenemaizeawebsiteformaizegeneprediction AT joetsjohann eugenemaizeawebsiteformaizegeneprediction |