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Manteia, a predictive data mining system for vertebrate genes and its applications to human genetic diseases
The function of genes is often evolutionarily conserved, and comparing the annotation of ortholog genes in different model organisms has proved to be a powerful predictive tool to identify the function of human genes. Here, we describe Manteia, a resource available online at http://manteia.igbmc.fr....
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3964984/ https://www.ncbi.nlm.nih.gov/pubmed/24038354 http://dx.doi.org/10.1093/nar/gkt807 |
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author | Tassy, Olivier Pourquié, Olivier |
author_facet | Tassy, Olivier Pourquié, Olivier |
author_sort | Tassy, Olivier |
collection | PubMed |
description | The function of genes is often evolutionarily conserved, and comparing the annotation of ortholog genes in different model organisms has proved to be a powerful predictive tool to identify the function of human genes. Here, we describe Manteia, a resource available online at http://manteia.igbmc.fr. Manteia allows the comparison of embryological, expression, molecular and etiological data from human, mouse, chicken and zebrafish simultaneously to identify new functional and structural correlations and gene-disease associations. Manteia is particularly useful for the analysis of gene lists produced by high-throughput techniques such as microarrays or proteomics. Data can be easily analyzed statistically to characterize the function of groups of genes and to correlate the different aspects of their annotation. Sophisticated querying tools provide unlimited ways to merge the information contained in Manteia along with the possibility of introducing custom user-designed biological questions into the system. This allows for example to connect all the animal experimental results and annotations to the human genome, and take advantage of data not available for human to look for candidate genes responsible for genetic disorders. Here, we demonstrate the predictive and analytical power of the system to predict candidate genes responsible for human genetic diseases. |
format | Online Article Text |
id | pubmed-3964984 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-39649842014-03-25 Manteia, a predictive data mining system for vertebrate genes and its applications to human genetic diseases Tassy, Olivier Pourquié, Olivier Nucleic Acids Res V. Human genome, model organisms, comparative genomics The function of genes is often evolutionarily conserved, and comparing the annotation of ortholog genes in different model organisms has proved to be a powerful predictive tool to identify the function of human genes. Here, we describe Manteia, a resource available online at http://manteia.igbmc.fr. Manteia allows the comparison of embryological, expression, molecular and etiological data from human, mouse, chicken and zebrafish simultaneously to identify new functional and structural correlations and gene-disease associations. Manteia is particularly useful for the analysis of gene lists produced by high-throughput techniques such as microarrays or proteomics. Data can be easily analyzed statistically to characterize the function of groups of genes and to correlate the different aspects of their annotation. Sophisticated querying tools provide unlimited ways to merge the information contained in Manteia along with the possibility of introducing custom user-designed biological questions into the system. This allows for example to connect all the animal experimental results and annotations to the human genome, and take advantage of data not available for human to look for candidate genes responsible for genetic disorders. Here, we demonstrate the predictive and analytical power of the system to predict candidate genes responsible for human genetic diseases. Oxford University Press 2014-01-01 2013-09-12 /pmc/articles/PMC3964984/ /pubmed/24038354 http://dx.doi.org/10.1093/nar/gkt807 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by/3.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | V. Human genome, model organisms, comparative genomics Tassy, Olivier Pourquié, Olivier Manteia, a predictive data mining system for vertebrate genes and its applications to human genetic diseases |
title | Manteia, a predictive data mining system for vertebrate genes and its applications to human genetic diseases |
title_full | Manteia, a predictive data mining system for vertebrate genes and its applications to human genetic diseases |
title_fullStr | Manteia, a predictive data mining system for vertebrate genes and its applications to human genetic diseases |
title_full_unstemmed | Manteia, a predictive data mining system for vertebrate genes and its applications to human genetic diseases |
title_short | Manteia, a predictive data mining system for vertebrate genes and its applications to human genetic diseases |
title_sort | manteia, a predictive data mining system for vertebrate genes and its applications to human genetic diseases |
topic | V. Human genome, model organisms, comparative genomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3964984/ https://www.ncbi.nlm.nih.gov/pubmed/24038354 http://dx.doi.org/10.1093/nar/gkt807 |
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