Author

Kazunari Kondo

National Institute of Health SciencesORCID 0000-0002-2662-4626Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Organism:plant (other)· 1 Assay:protein sequence· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Hiroyuki Hanada· 1 shared Ichiro TakeuchiiD· 1 shared Jumpei NarushimaiD· 1 shared Keisuke SogaiD· 1 shared Kento Goto· 1 shared Kôsuke NakamuraiD· 1 shared Norihito ShibataiD· 1 shared Norimasa Tamehiro· 1 shared

Activity by Year

2021-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperBioinformatics

Hiroyuki Hanada

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintAug 17, 2021

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

Kento Goto, Norimasa Tamehiro, Takumi Yoshida…·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.

1 citation

protein sequencemachine learning (classical)

𝕏 PostBluesky

BioinformaticsbioRxivPreprintMay 28, 2021

Strategy for detecting off-target sites in genome-edited rice

Jumpei Narushima, Shinya Kimata, Yuh Shiwa…·Kazunari Kondo

This study introduces SITE-Seq, a method to detect off-target sites in genome-edited rice, and shows it identifies mutations not found by in silico tools.

2 citations

plant (other)whole-genome sequencing

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