machine learning

QTG-Finder: A Machine-Learning Based Algorithm To Prioritize Causal Genes of Quantitative Trait Loci in Arabidopsis and Rice
Fan Lin, Jue Fan, Seung Y. Rhee

G3: Genes, Genomes, Genetics July 2019 g3.400319.2019; https://doi.org/10.1534/g3.119.400319
diploS/HIC: An Updated Approach to Classifying Selective Sweeps

Andrew D. Kern, Daniel R. Schrider

G3: Genes, Genomes, Genetics June 2018 8: 1959-1970; https://doi.org/10.1534/g3.118.200262
Application of Response Surface Methods To Determine Conditions for Optimal Genomic Prediction
Réka Howard, Alicia L. Carriquiry, William D. Beavis

G3: Genes, Genomes, Genetics September 2017 7: 3103-3113; https://doi.org/10.1534/g3.117.044453
Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning
Tanel Pärnamaa, Leopold Parts

G3: Genes, Genomes, Genetics May 2017 7: 1385-1392; https://doi.org/10.1534/g3.116.033654
Assessing Predictive Properties of Genome-Wide Selection in Soybeans
Alencar Xavier, William M. Muir, Katy Martin Rainey

G3: Genes, Genomes, Genetics August 2016 6: 2611-2616; https://doi.org/10.1534/g3.116.032268
A Resource of Quantitative Functional Annotation for Homo sapiens Genes
Murat Taşan, Harold J. Drabkin, John E. Beaver, Hon Nian Chua, Julie Dunham, Weidong Tian, Judith A. Blake, Frederick P. Roth

G3: Genes, Genomes, Genetics February 2012 2: 223-233; https://doi.org/10.1534/g3.111.000828

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