Kentaro K. Shimizu

This study introduces a complex-valued representation for time-series gene expression data, showing it captures distinct gene-gene similarities and temporal programs comparable to conventional methods.

This study identifies genetic factors influencing pollen number and anther length in bread wheat using nested association mapping, revealing new QTLs and the role of Green Revolution genes.

The paper shows that genetic diversity is inversely correlated with linguistic diversity, with isolation promoting linguistic diversification and contact promoting homogenization.

The paper quantifies spatial disease variation in barley and links it to neighbor genotypes, finding significant genetic variants that reduce disease damage through allelic mixtures.

This paper introduces HOBIT, a statistical method to detect shifts in homeolog expression ratios in allopolyploids, outperforming existing methods in simulation and real data applications.

The paper uses genetic admixture to estimate language contact effects globally, finding shared features between admixed populations and language pairs in the same area.

This study uses Lasy-Seq to analyze transcriptomic variation in 25 common wheat accessions, revealing cis- and trans-regulation patterns across subgenomes and tissues.

This study annotates the wheat pan-transcriptome de novo and identifies gene diversity and expression patterns across multiple wheat cultivars and tissues.

The paper presents an improved genome assembly for the saguaro cactus using long-read PacBio data, increasing size and gene count.

ARPEGGIO provides an automated workflow for analyzing epigenetic data in polyploids, improving accuracy and reproducibility in DNA methylation analysis of allopolyploids.

This paper introduces Neighbor GWAS, a method that incorporates neighbor genotypic identity into GWAS to better capture spatial genetic effects, finding that neighbor effects explain 8% more phenotypic variation in field herbivory data.

This study analyzes the genetic structure of 177 individuals from the Andes, Amazonia, and Pacific Coast of South America, revealing complex ancestry patterns and recent gene flow across regions.

This study compares RNA-seq expression quantification methods for allopolyploids, finding that subgenome-classification approaches significantly reduce error rates compared to standard methods.