Cargando…

Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes

Genetics and “omics” studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the li...

Descripción completa

Detalles Bibliográficos
Autores principales: Hassani-Pak, Keywan, Rawlings, Christopher
Formato: Online Artículo Texto
Lenguaje:English
Publicado: De Gruyter 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042805/
https://www.ncbi.nlm.nih.gov/pubmed/28609292
http://dx.doi.org/10.1515/jib-2016-0002
_version_ 1783339224518361088
author Hassani-Pak, Keywan
Rawlings, Christopher
author_facet Hassani-Pak, Keywan
Rawlings, Christopher
author_sort Hassani-Pak, Keywan
collection PubMed
description Genetics and “omics” studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.
format Online
Article
Text
id pubmed-6042805
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher De Gruyter
record_format MEDLINE/PubMed
spelling pubmed-60428052019-01-28 Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes Hassani-Pak, Keywan Rawlings, Christopher J Integr Bioinform Review Genetics and “omics” studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future. De Gruyter 2017-06-13 /pmc/articles/PMC6042805/ /pubmed/28609292 http://dx.doi.org/10.1515/jib-2016-0002 Text en ©2017, Keywan Hassani-Pak, published by De Gruyter, Berlin/Boston http://creativecommons.org/licenses/by-nc-nd/3.0 This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
spellingShingle Review
Hassani-Pak, Keywan
Rawlings, Christopher
Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes
title Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes
title_full Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes
title_fullStr Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes
title_full_unstemmed Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes
title_short Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes
title_sort knowledge discovery in biological databases for revealing candidate genes linked to complex phenotypes
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6042805/
https://www.ncbi.nlm.nih.gov/pubmed/28609292
http://dx.doi.org/10.1515/jib-2016-0002
work_keys_str_mv AT hassanipakkeywan knowledgediscoveryinbiologicaldatabasesforrevealingcandidategeneslinkedtocomplexphenotypes
AT rawlingschristopher knowledgediscoveryinbiologicaldatabasesforrevealingcandidategeneslinkedtocomplexphenotypes