Author

Atsushi Hijikata

Tokyo University of Pharmacy and Life SciencesORCID 0000-0003-4297-8368Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Biochemistry· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1 Research Focus:variant calling· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

Ayaka Noguchi· 1 shared Ayako FukunakaiD· 1 shared Bangzhong LiniD· 1 shared Eiji NanbaiD· 1 shared Emi Yoshigai· 1 shared Gen TanakaiD· 1 shared Hideo SasaiiD· 1 shared Hiroki TaguchiiD· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperBiochemistry

Ayaka Noguchi

Mutual co-authors in cluster

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2 papers

Recent·Most cited

BiochemistrybioRxivPreprintOct 23, 2025

Discovery of a Selective Inhibitor of ZIP14 with Therapeutic Potential for Cancer-associated Cachexia

Takafumi Hara, Gen Tanaka, Tomonori Tamura…·Toshiyuki Fukada

This paper identifies PPTD, the first selective ZIP14 inhibitor, showing it reverses ZIP14-driven cytotoxicity and ameliorates cancer cachexia in mice.

DOI 10.1101/2025.10.23.682519

mousedeep learning

𝕏 PostBluesky

GenomicsNucleic Acids ResearchPeer-reviewedNov 14, 2023

Exome-wide benchmark of difficult-to-sequence regions using short-read next-generation DNA sequencing

Atsushi Hijikata, Mikita Suyama, Shingo Kikugawa…·Osamu Ohara

The paper benchmarks difficult-to-sequence regions in the human exome using machine learning and real-world NGS data from gnomAD to improve clinical sequencing accuracy.

14 citations

humanwhole-exome sequencing

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