Kentaro Tomii

Prot-LAMBDA improves protein structure prediction by explicitly incorporating spatial relationships, achieving better performance than ESM2-3B in contact prediction and 3D structure prediction.

zsasa computes solvent accessible surface area at proteome scale using a fast, open-source Zig-based engine, outperforming existing tools in speed and memory efficiency.

The paper fits the Gompertz curve to PDB growth data to estimate future PDB entries and protein folds, revealing a deceleration in growth.

This study shows that PIKfyve inhibition leads to LRRK2 hyperactivation through PI3P and CASM, revealing a new mechanism involving membrane lipids and Rab proteins.

This study compares β-catenin sequences and function across nonbilaterian metazoans and Xenopus embryos, revealing conserved structural and functional properties of β-catenin complexes.

This study investigates the functions of neurexins in the cnidarian Nematostella vectensis, revealing both neuronal and non-neuronal roles in synaptic and cell adhesion processes.

Meta-Align improves DNA sequence alignment by incorporating quality scores and handling frameshift errors using an HMM-based approach, outperforming TBLASTX in simulated benchmarks.

The paper introduces a deep neural network for protein contact prediction that directly uses multiple sequence alignments to extract correlation information and improve accuracy over traditional ECA methods.

The paper improves PSI-BLAST performance by adjusting sequence weight calculation to avoid narrow blocks, showing significant gains in benchmark tests.