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Bioinformatics methods for identifying candidate disease genes

With the explosion in genomic and functional genomics information, methods for disease gene identification are rapidly evolving. Databases are now essential to the process of selecting candidate disease genes. Combining positional information with disease characteristics and functional information i...

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Detalles Bibliográficos
Autores principales: van Driel, Marc A, Brunner, Han G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3525160/
https://www.ncbi.nlm.nih.gov/pubmed/16848981
http://dx.doi.org/10.1186/1479-7364-2-6-429
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author van Driel, Marc A
Brunner, Han G
author_facet van Driel, Marc A
Brunner, Han G
author_sort van Driel, Marc A
collection PubMed
description With the explosion in genomic and functional genomics information, methods for disease gene identification are rapidly evolving. Databases are now essential to the process of selecting candidate disease genes. Combining positional information with disease characteristics and functional information is the usual strategy by which candidate disease genes are selected. Enrichment for candidate disease genes, however, depends on the skills of the operating researcher. Over the past few years, a number of bioinformatics methods that enrich for the most likely candidate disease genes have been developed. Such in silico prioritisation methods may further improve by completion of datasets, by development of standardised ontologies across databases and species and, ultimately, by the integration of different strategies.
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spelling pubmed-35251602012-12-19 Bioinformatics methods for identifying candidate disease genes van Driel, Marc A Brunner, Han G Hum Genomics Software Review With the explosion in genomic and functional genomics information, methods for disease gene identification are rapidly evolving. Databases are now essential to the process of selecting candidate disease genes. Combining positional information with disease characteristics and functional information is the usual strategy by which candidate disease genes are selected. Enrichment for candidate disease genes, however, depends on the skills of the operating researcher. Over the past few years, a number of bioinformatics methods that enrich for the most likely candidate disease genes have been developed. Such in silico prioritisation methods may further improve by completion of datasets, by development of standardised ontologies across databases and species and, ultimately, by the integration of different strategies. BioMed Central 2006-06-01 /pmc/articles/PMC3525160/ /pubmed/16848981 http://dx.doi.org/10.1186/1479-7364-2-6-429 Text en Copyright ©2006 Henry Stewart Publications
spellingShingle Software Review
van Driel, Marc A
Brunner, Han G
Bioinformatics methods for identifying candidate disease genes
title Bioinformatics methods for identifying candidate disease genes
title_full Bioinformatics methods for identifying candidate disease genes
title_fullStr Bioinformatics methods for identifying candidate disease genes
title_full_unstemmed Bioinformatics methods for identifying candidate disease genes
title_short Bioinformatics methods for identifying candidate disease genes
title_sort bioinformatics methods for identifying candidate disease genes
topic Software Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3525160/
https://www.ncbi.nlm.nih.gov/pubmed/16848981
http://dx.doi.org/10.1186/1479-7364-2-6-429
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