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GFINDer: genetic disease and phenotype location statistical analysis and mining of dynamically annotated gene lists

Phenotype analysis is commonly recognized to be of great importance for gaining insight into genetic interaction underlying inherited diseases. However, few computational contributions have been proposed for this purpose, mainly owing to lack of controlled clinical information easily accessible and...

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Detalles Bibliográficos
Autores principales: Masseroli, Marco, Galati, Osvaldo, Pinciroli, Francesco
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1160215/
https://www.ncbi.nlm.nih.gov/pubmed/15980570
http://dx.doi.org/10.1093/nar/gki454
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author Masseroli, Marco
Galati, Osvaldo
Pinciroli, Francesco
author_facet Masseroli, Marco
Galati, Osvaldo
Pinciroli, Francesco
author_sort Masseroli, Marco
collection PubMed
description Phenotype analysis is commonly recognized to be of great importance for gaining insight into genetic interaction underlying inherited diseases. However, few computational contributions have been proposed for this purpose, mainly owing to lack of controlled clinical information easily accessible and structured for computational genome-wise analyses. We developed and made available through GFINDer web server an original approach for the analysis of genetic disorder related genes by exploiting the information on genetic diseases and their clinical phenotypes present in textual form within the Online Mendelian Inheritance in Man (OMIM) database. Because several synonyms for the same name and different names for overlapping concepts are often used in OMIM, we first normalized phenotype location descriptions reducing them to a list of unique controlled terms representing phenotype location categories. Then, we hierarchically structured them and the correspondent genetic diseases according to their topology and granularity of description, respectively. Thus, in GFINDer we could implement specific Genetic Disorders modules for the analysis of these structured data. Such modules allow to automatically annotate user-classified gene lists with updated disease and clinical information, classify them according to the genetic syndrome and the phenotypic location categories, and statistically identify the most relevant categories in each gene class. GFINDer is available for non-profit use at .
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spelling pubmed-11602152005-06-29 GFINDer: genetic disease and phenotype location statistical analysis and mining of dynamically annotated gene lists Masseroli, Marco Galati, Osvaldo Pinciroli, Francesco Nucleic Acids Res Article Phenotype analysis is commonly recognized to be of great importance for gaining insight into genetic interaction underlying inherited diseases. However, few computational contributions have been proposed for this purpose, mainly owing to lack of controlled clinical information easily accessible and structured for computational genome-wise analyses. We developed and made available through GFINDer web server an original approach for the analysis of genetic disorder related genes by exploiting the information on genetic diseases and their clinical phenotypes present in textual form within the Online Mendelian Inheritance in Man (OMIM) database. Because several synonyms for the same name and different names for overlapping concepts are often used in OMIM, we first normalized phenotype location descriptions reducing them to a list of unique controlled terms representing phenotype location categories. Then, we hierarchically structured them and the correspondent genetic diseases according to their topology and granularity of description, respectively. Thus, in GFINDer we could implement specific Genetic Disorders modules for the analysis of these structured data. Such modules allow to automatically annotate user-classified gene lists with updated disease and clinical information, classify them according to the genetic syndrome and the phenotypic location categories, and statistically identify the most relevant categories in each gene class. GFINDer is available for non-profit use at . Oxford University Press 2005-07-01 2005-06-27 /pmc/articles/PMC1160215/ /pubmed/15980570 http://dx.doi.org/10.1093/nar/gki454 Text en © The Author 2005. Published by Oxford University Press. All rights reserved
spellingShingle Article
Masseroli, Marco
Galati, Osvaldo
Pinciroli, Francesco
GFINDer: genetic disease and phenotype location statistical analysis and mining of dynamically annotated gene lists
title GFINDer: genetic disease and phenotype location statistical analysis and mining of dynamically annotated gene lists
title_full GFINDer: genetic disease and phenotype location statistical analysis and mining of dynamically annotated gene lists
title_fullStr GFINDer: genetic disease and phenotype location statistical analysis and mining of dynamically annotated gene lists
title_full_unstemmed GFINDer: genetic disease and phenotype location statistical analysis and mining of dynamically annotated gene lists
title_short GFINDer: genetic disease and phenotype location statistical analysis and mining of dynamically annotated gene lists
title_sort gfinder: genetic disease and phenotype location statistical analysis and mining of dynamically annotated gene lists
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1160215/
https://www.ncbi.nlm.nih.gov/pubmed/15980570
http://dx.doi.org/10.1093/nar/gki454
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