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Perspective

Artificial Intelligence and Integrated Genotype–Phenotype Identification

by 1,2
1
Department of Public Health Sciences, Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC 29425, USA
2
Health Equity and Rural Outreach Innovation Center (HEROIC), Ralph H. Johnson Veteran Affairs Medical Center, Charleston, SC 29401, USA
Genes 2019, 10(1), 18; https://doi.org/10.3390/genes10010018
Received: 9 December 2018 / Revised: 20 December 2018 / Accepted: 21 December 2018 / Published: 28 December 2018
(This article belongs to the Special Issue Systems Analytics and Integration of Big Omics Data)
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. View Full-Text
Keywords: artificial intelligence; genotype; phenotype; deep phenotype; data integration; genomics; phenomics; precision medicine informatics artificial intelligence; genotype; phenotype; deep phenotype; data integration; genomics; phenomics; precision medicine informatics
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MDPI and ACS Style

Frey, L.J. Artificial Intelligence and Integrated Genotype–Phenotype Identification. Genes 2019, 10, 18. https://doi.org/10.3390/genes10010018

AMA Style

Frey LJ. Artificial Intelligence and Integrated Genotype–Phenotype Identification. Genes. 2019; 10(1):18. https://doi.org/10.3390/genes10010018

Chicago/Turabian Style

Frey, Lewis J. 2019. "Artificial Intelligence and Integrated Genotype–Phenotype Identification" Genes 10, no. 1: 18. https://doi.org/10.3390/genes10010018

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