📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

An evaluation of machine-learning for predicting phenotype: studies in yeast, rice, and wheat. (2020)

First Author: Grinberg NF

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1007/s10994-019-05848-5

PubMed Identifier: 32174648

Publication URI: http://europepmc.org/abstract/MED/32174648

Type: Journal Article/Review

Volume: 109

Parent Publication: Machine learning

Issue: 2

ISSN: 0885-6125