Yuki Iwasaki

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.

Time-series trend of pandemic SARS-CoV-2 variants visualized using batch-learning self-organizing map for oligonucleotide compositions

The paper uses batch-learning self-organizing maps to analyze SARS-CoV-2 genome sequences and visualize time-series trends of variant populations.

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.

Intron retention as a new marker of the pre-disease state and its recovery to the normal state by a traditional Japanese multi-herbal medicine

The paper identifies intron retention as a marker of pre-disease and aging states and shows recovery by a traditional herbal medicine in klotho mice.

A unique neurogenomic state emerges after aggressive confrontations in males of the fish Betta splendens

The paper examines how brain-transcriptomic profiles change in male Betta splendens after aggressive confrontations, revealing a unique basal neurogenomic state with reduced gene expression variation.

Human cell-dependent, directional, time-dependent changes in the mono- and oligonucleotide compositions of SARS-CoV-2 genomes

The paper analyzes how SARS-CoV-2 genome mono- and oligonucleotide compositions change over time in human cells and compares them to other coronaviruses.