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Artificial Intelligence and Integrated Genotype–Phenotype Identification

The integration of phenotypes and genotypes is at an unprecedented level and offers new opportunities to establish deep phenotypes. There are a number of challenges to overcome, specifically, accelerated growth of data, data silos, incompleteness, inaccuracies, and heterogeneity within and across da...

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Detalles Bibliográficos
Autor principal: Frey, Lewis J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6356893/
https://www.ncbi.nlm.nih.gov/pubmed/30597900
http://dx.doi.org/10.3390/genes10010018
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author Frey, Lewis J.
author_facet Frey, Lewis J.
author_sort Frey, Lewis J.
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description The integration of phenotypes and genotypes is at an unprecedented level and offers new opportunities to establish deep phenotypes. There are a number of challenges to overcome, specifically, accelerated growth of data, data silos, incompleteness, inaccuracies, and heterogeneity within and across data sources. This perspective report discusses artificial intelligence (AI) approaches that hold promise in addressing these challenges by automating computable phenotypes and integrating them with genotypes. Collaborations between biomedical and AI researchers will be highlighted in order to describe initial successes with an eye toward the future.
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spelling pubmed-63568932019-02-04 Artificial Intelligence and Integrated Genotype–Phenotype Identification Frey, Lewis J. Genes (Basel) Perspective The integration of phenotypes and genotypes is at an unprecedented level and offers new opportunities to establish deep phenotypes. There are a number of challenges to overcome, specifically, accelerated growth of data, data silos, incompleteness, inaccuracies, and heterogeneity within and across data sources. This perspective report discusses artificial intelligence (AI) approaches that hold promise in addressing these challenges by automating computable phenotypes and integrating them with genotypes. Collaborations between biomedical and AI researchers will be highlighted in order to describe initial successes with an eye toward the future. MDPI 2018-12-28 /pmc/articles/PMC6356893/ /pubmed/30597900 http://dx.doi.org/10.3390/genes10010018 Text en © 2018 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Perspective
Frey, Lewis J.
Artificial Intelligence and Integrated Genotype–Phenotype Identification
title Artificial Intelligence and Integrated Genotype–Phenotype Identification
title_full Artificial Intelligence and Integrated Genotype–Phenotype Identification
title_fullStr Artificial Intelligence and Integrated Genotype–Phenotype Identification
title_full_unstemmed Artificial Intelligence and Integrated Genotype–Phenotype Identification
title_short Artificial Intelligence and Integrated Genotype–Phenotype Identification
title_sort artificial intelligence and integrated genotype–phenotype identification
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6356893/
https://www.ncbi.nlm.nih.gov/pubmed/30597900
http://dx.doi.org/10.3390/genes10010018
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