Author

Motomu Matsui

The University of TokyoORCID 0000-0001-5077-4977Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:whole-genome sequencing· 2 Organism:bacteria (other)· 1 Approach:machine learning (classical)· 1 Research Focus:phylogenetics / evolution· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1 Organism:virus· 1

Frequent Co-Authors

Hirotaka MatsumotoiD· 1 shared Kento TominagaiD· 1 shared Seiji Toki· 1 shared Takao SuzukiiD· 1 shared Takashi TsuchimatsuiD· 1 shared Wataru IwasakiiD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 10 mutual co-author links

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1 shared paperBioinformatics

Hirotaka MatsumotoORCID

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2 papers

Recent·Most cited

GenomicsmSystemsPeer-reviewedApr 3, 2026

Genomic and evolutionary factors influencing the prediction accuracy of optimal growth temperature in prokaryotes

Seiji Toki, Motomu Matsui, Kento Tominaga…·Wataru Iwasaki

This study develops a model to predict optimal growth temperature in prokaryotes using genomic data, finding that incorporating gene presence/absence improves accuracy for psychrophiles.

3 citationstop 4%

bacteria (other)whole-genome sequencing

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BioinformaticsbioRxivPreprintMay 29, 2022

PhyGraFT: a network-based method for phylogenetic trait analysis

Hirotaka Matsumoto, Motomu Matsui

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

DOI 10.1101/2022.05.29.493939

viruswhole-genome sequencing

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