Arthur Korte

This study observes rapid genetic adaptation and population dynamics in Arabidopsis thaliana across diverse climates over 5 years, showing predictable adaptation trends linked to survival and extinction risks.

permGWAS2 improves permutation-based GWAS by reducing computational demands and accounting for population structure, achieving lower false discovery rates.

The paper introduces permGWAS, a permutation-based GWAS method that improves significance thresholds for skewed phenotypes and reduces false discovery rates compared to Bonferroni correction.

This paper proposes local convolutional neural networks for genomic prediction, showing improved performance over traditional methods in most cases, especially with medium complexity traits and large datasets.

The paper identifies CPT3 and ABH genes associated with dolichol accumulation in Arabidopsis using GWAS and QTL mapping, with experimental validation.

The paper benchmarks seven chloroplast genome assembly tools, finding significant performance differences and assembling 20 novel chloroplast genomes from 105 datasets.

GWAS-Flow is a GPU-accelerated framework for efficient permutation-based GWAS, outperforming custom scripts in speed without loss of accuracy.