Author

Takumi Yoshida

Nagoya Institute of TechnologyPrimary ORCID profile (0009-0002-5743-3002 · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Same name, identified by ORCID

Takumi YoshidaiD1 paper · Shinshu University

Biology Disciplines

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Bioengineering· 1 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1 Assay:protein sequence· 1 Organism:rat· 1

Frequent Co-Authors

Daisuke Naruse· 1 shared Hiroyuki Hanada· 1 shared Hiroyuki Kamiya· 1 shared Hiroyuki MiyamotoiD· 1 shared Ichiro TakeuchiiD· 1 shared Kazunari KondoiD· 1 shared Kento Goto· 1 shared Kyohei OyamaiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperBioengineering

Daisuke Naruse

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2 papers

Recent·Most cited

Characterizing in vivo degradation of electrospun biodegradable nanofibers by size-exclusion chromatography

Shingo Kunioka, Takumi Yoshida, Daisuke Naruse, Yuki Setogawa, Hiroyuki Miyamoto, Ryohei Ushioda, Yuta Kikuchi, Masahiro Tsutsui, Hiroyuki Kamiya, Kyohei Oyama

This study quantifies the in vivo degradation of biodegradable nanofibers using size-exclusion chromatography, revealing material- and environment-dependent degradation patterns.

bioRxiv · May 13, 2026 · PreprintBioengineering

AllerStat: Finding Statistically Significant Allergen-Specific Patterns in Protein Sequences by Machine Learning

Kento Goto, Norimasa Tamehiro, Takumi Yoshida, Hiroyuki Hanada, Takuto Sakuma, Reiko Adachi, Kazunari Kondo, Ichiro Takeuchi

The paper introduces a machine learning method to identify statistically significant allergen-specific amino-acid sequences in proteins, achieving higher allergenicity prediction accuracy than existing approaches.

bioRxiv · Aug 17, 2021 · PreprintBioinformatics