Author

Naoya Ishibashi

Institute of Science Tokyo HospitalORCID 0009-0008-5533-7096Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:software / tool· 1 Research Focus:variant effect prediction· 1 Assay:whole-exome sequencing· 1

Frequent Co-Authors

Fuyuki MiyaiD· 1 shared Haruko NakagawaiD· 1 shared Michina Morioka· 1 shared Sadakatsu IkedaiD· 1 shared Satoru Aoyama· 1 shared Takashi KamataniiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 15 mutual co-author links

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1 shared paperBioinformatics

Fuyuki MiyaORCID

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1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintJul 10, 2026

MARiO: predicting cancer variant pathogenicity by integrating in silico evaluation and patient-level mutational contexts

Haruko Nakagawa, Takashi Kamatani, Naoya Ishibashi…·Sadakatsu Ikeda

MARiO predicts cancer missense variant pathogenicity by integrating variant-level features and patient-level clinical and genomic contexts, achieving high accuracy.

DOI 10.64898/2026.07.07.736919

humanwhole-exome sequencing

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