Kyoto University Graduate School of Medicine, Kyoto University Big Data Medical Science, Okuno Laboratory
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Early-Run Confidence-Based Computational Budget Triage for Antibody-Antigen Complex Structure Prediction

2026.10.27 POSTER
CBI Society Annual Meeting 2026 (Poster, P06-26)

Kyoka Iyanaga, Seungeon Lee, Takuto Koyama, Tomoaki Shima, Itsuki Maeda, Hiroki Shirai, Shigeyuki Matsumoto, Yasushi Okuno.

Overview

Poster at the CBI Society Annual Meeting 2026, presented by Kyoka Iyanaga. Stochastic structure predictors find a correct antibody–antigen complex more often with more runs, but at higher cost; this work tests whether confidence available after only a few runs can drive an adaptive decision to stop or continue.

Session: P06 “Drug Discovery Application” (P06-26, core time B: Oct 27 17:00–18:00 / Oct 28 16:00–17:00)

Affiliation: Kyoto University Graduate School of Medicine, Department of Biomedical Data Intelligence

Poster list (EN) Poster list (JP) Abstract Abstracts (PDF)