Lynn Johnson

reelGene evaluates gene models using machine learning and evolutionary data, finding 28% of maize gene models are incorrectly annotated or nonfunctional.

The paper identifies selection signatures and predicts deleterious mutations in common bean using phylogenetic analysis and machine learning, showing correlations with agronomic traits.

In a mouse model of focal epilepsy, sub-surface laser-produced cuts encircling the seizure focus attenuate propagation without behavioral impairment.

The paper introduces the Practical Haplotype Graph (PHG) platform for storing and using pangenomes, demonstrating its effectiveness in imputing genomes from low-coverage data in crops like maize.

AnchorWave improves genome alignment for genomes with high diversity, structural polymorphism, and whole-genome duplication by using a duplication-informed algorithm and gap cost strategy.

The paper develops models to predict protein temperature adaptation across prokaryotes and eukaryotes, finding site-specific models best transfer across the divide.

The paper develops a multiple genome alignment workflow for plants, showing that k-mer masking and parameter tuning improve alignment of functional regions.

The paper constructs a maize pangenome haplotype graph (PHG) to improve genotype imputation accuracy across diverse germplasm using WGS and GBS data.

This paper introduces a sorghum Practical Haplotype Graph (PHG) that enables accurate SNP calling and imputation from low-coverage sequencing data, improving genomic prediction accuracy and reducing genotyping costs.

This study identifies independent temperate adaptations in maize flowering time across different populations using GWAS and machine learning.