Molly S. Megraw

The paper develops a machine learning framework to predict maize pollen fitness phenotypes using genomic and expression data, finding that expression specificity is a critical feature for accurate predictions.

The paper shows pollen fitness alleles in maize affect spatial inheritance patterns across ears, with non-Mendelian transmission trends observed in specific mutants.

The paper identifies cis-regulatory determinants of tissue-specific gene expression in Arabidopsis thaliana by analyzing TSS-seq, OC-seq, and RNA-seq data, finding that TSS-proximal TF binding sites are more important than distal chromatin regions.

IndeCut evaluates network motif discovery algorithms to determine their performance and guide tool selection for any network of interest.