Kennosuke Wada

Unsupervised explainable AI reveals similar oligonucleotide-usage zones matching the highest-resolution human chromosome bands

The paper uses unsupervised AI to identify oligonucleotide-usage zones in the human genome that match high-resolution chromosomal banding patterns.

AI-based search for convergently expanding, advantageous mutations in SARS-CoV-2 by focusing on oligonucleotide frequencies

The paper identifies advantageous mutations in SARS-CoV-2 by analyzing convergent expansions of oligonucleotide frequencies using BLSOM.

Unsupervised explainable AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome

The paper introduces BLSOM for analyzing genome sequences, revealing novel insights in SARS-CoV-2, metagenomics, and human genomes.

Time-series analyses of directional sequence changes in SARS-CoV-2 genomes and an efficient search method for advantageous mutations for growth in human cells

The paper analyzes SARS-CoV-2 genome composition changes over time and identifies seven mutations potentially advantageous for human cell growth.