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Evolutionarily informed machine learning enhances the power of predictive gene-to-phenotype relationships
- Source :
- Nature Communications, Vol 12, Iss 1, Pp 1-15 (2021)
- Publication Year :
- 2021
- Publisher :
- Nature Portfolio, 2021.
-
Abstract
- Predicting complex phenotypes from genomic information is still a challenge. Here, the authors use an evolutionarily informed machine learning approach within and across species to predict genes affecting nitrogen utilization in crops, and show their approach is also useful in mammalian systems.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 12
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f8c1a08be1a4c64bc07660726b1c1e2
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-021-25893-w