Jeremy Pardo

This study analyzes drought gene expression datasets and finds they are inconsistent, proposing classifiers to detect drought stress and advocating for standardized protocols.

The paper identifies a core set of 744 stress-responsive genes in maize across six abiotic stresses using RNAseq data and machine learning, highlighting transcription factors as key regulators.

This study predicts complex traits in maize using transcriptome and genetic marker data, finding similar performance between both approaches and highlighting transcriptome's role in capturing trait variation not captured by sequence data.