John P. Lloyd

The paper models transcriptional responses to heat and drought stress in Arabidopsis thaliana using machine learning and deep learning, identifying cis-regulatory elements that predict gene response patterns.

The paper evaluates intergenic transcribed regions (ITRs) in Poaceae species to determine if they represent functional genes or noisy transcription, finding most ITRs lack conservation and are likely nonfunctional.

The paper predicts cell-cycle expressed genes in S. cerevisiae using regulatory data, identifying both canonical and non-canonical regulators of time-specific expression.

The paper identifies intergenic transcribed regions (ITRs) in 15 flowering plant species and uses machine learning to classify them as functional or non-functional based on sequence and evolutionary features.