Nikee Shrestha

The paper develops a sequence-based classifier to identify phenotype-associated genes in plants, validated across maize, rice, and arabidopsis.

This study identifies genetic determinants of flowering time variation in sorghum using genome and transcriptome-wide association studies, revealing conserved gene functions but non-orthologous gene involvement compared to related species.

This study identifies genetic variants associated with photosynthetic traits in maize by controlling environmental and spatial confounders, revealing high-confidence GWAS signals and validating candidate genes through insertion alleles.

The paper identifies genomic intervals and transcripts associated with metabolite abundance variation in maize under field conditions using GWAS and transcriptome-wide association studies.

This study uses 3D reconstruction from 2D images to measure phyllotaxy in sorghum, showing its feasibility for genetic analysis and breeding.

The paper uses image analysis models to quantify seed color in sorghum, finding they outperform human assessment and identify more genomic signals linked to seed color genes.

This study uses comparative GWAS to identify genes influencing NPQ kinetics in sorghum, maize, and Arabidopsis, revealing a Mendelian gene involved in pigment degradation.

The paper uses a transformer model to predict gene expression patterns across plant organs and identifies regulatory regions in maize and sorghum genomes.

This study identifies genetic loci in sorghum that influence human gut microbiome composition through in vitro fermentation of grain.