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...

Full description

Saved in:
Bibliographic Details
Published in:Genes 2018-12, Vol.10 (1), p.18
Main Author: Frey, Lewis J
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Biomedical research
Cognition & reasoning
Deep learning
Dimensional analysis
Electronic health records
Genomics
Genotype & phenotype
Genotypes
Human performance
Knowledge representation
Mutation
Ontology
Phenotypes
Proteins
Random access memory
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2073-4425
2073-4425
DOI:10.3390/genes10010018