Author

Toshimichi Ikemura

Nagahama Institute of Bio-Science and TechnologyORCID 0000-0001-9931-172XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 5 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 6 Assay:whole-genome sequencing· 6 Organism:human· 5 Research Focus:clustering· 3 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Research Focus:dimensionality reduction· 1 Assay:DNA methylation· 1

Frequent Co-Authors

Takashi AbeiD· 5 shared Yuki Iwasaki· 5 shared Kennosuke Wada· 4 shared Yoshiko Wada· 4 shared Ryuki Furukawa· 1 shared

Activity by Year

2020-2026 · peak 3/yr

Co-Author Collaboration Network

5 top collaborators · 8 mutual co-author links

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5 shared papersBioinformatics

Takashi AbeORCID

Mutual co-authors in cluster

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6 papers

Recent·Most cited

GenomicsbioRxivPreprintMar 11, 2026

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

Toshimichi Ikemura, Yuki Iwasaki, Kennosuke Wada…·Takashi Abe

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

DOI 10.64898/2026.03.09.710446

humanDNA methylation

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BioinformaticsPLoS ONEPeer-reviewedAug 31, 2022

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

Toshimichi Ikemura, Yuki Iwasaki, Kennosuke Wada…·Takashi Abe

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

3 citations

viruswhole-genome sequencing

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BioinformaticsData Science JournalPeer-reviewedSep 21, 2021

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

Takashi Abe, Ryuki Furukawa, Yuki Iwasaki, Toshimichi Ikemura

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

7 citations

humanwhole-genome sequencing

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BioinformaticsGenes & Genetic SystemsPeer-reviewedAug 1, 2021

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

Toshimichi Ikemura, Yuki Iwasaki, Kennosuke Wada…·Takashi Abe

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

8 citations

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BioinformaticsBMC MicrobiologyPeer-reviewedMar 23, 2021

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

Yuki Iwasaki, Takashi Abe, Toshimichi Ikemura

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

13 citations

humanwhole-genome sequencing

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BioinformaticsGenePeer-reviewedAug 6, 2020

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

Kennosuke Wada, Yoshiko Wada, Toshimichi Ikemura

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

18 citations

humanwhole-genome sequencing

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