Hirotaka Matsumoto

This study characterizes repeat architectures in protozoan parasites, identifying lineage-specific clusters with distinct complexity patterns and functional roles.

PhyGraFT analyzes trait data using a network-based approach to identify phylogenetic signals and trait associations in viral and bacterial data.

The paper introduces MOCCS profiles to analyze DNA-binding specificity of TFs across cell types and shows that one-third of TFs exhibit cell-type-specific binding, with ΔMOCCS2scores predicting variant effects on TF binding.

The paper models C. elegans thermotactic steering behavior using a neuroanatomical model and evolutionary algorithm, finding that persistent thermal signals modulate steering rates to guide movement toward a target temperature.

This paper introduces a novel metric for hyperbolic phylogenetic tree embeddings and demonstrates its effectiveness in reconstructing evolutionary distances and predicting nearest-neighbor nodes.

The paper introduces an NMF-based method to identify overlooked differentially expressed gene regions in single-cell RNA-seq data, finding novel transcripts related to neural stem/progenitor cell differentiation.

The paper develops an efficient algorithm to infer gene regulatory networks in Drosophila melanogaster embryogenesis, identifying key regulatory interactions and demonstrating its computational efficiency.

SCODE infers gene regulatory networks from single-cell RNA-Seq data during differentiation, showing improved performance and efficiency compared to existing methods.