ショートアブストラクト一覧
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招待講演者（プログラム順）
Prof. Jürgen Bajorath（University of Bonn）
“Chemical Language Models and Prediction Anatomy“
Prof. Alexander Tropsha（The University of North Carolina at Chapel Hill）
“AI/ML approaches for generative chemical design and virtual screening acceleration“
Prof. Yoshihiro Yamanishi （Nagoya University）
“Data-driven drug search and design by machine learning”
Prof. Yasushi Okuno（Kyoto University）
“DX platform for target discovery and drug design“
Dr. Sharon Bryant（Inte:Ligand）
“Advanced 3D-Pharmacophores for Drug Discovery and De-Risking Neurotoxicity“
Prof. Gisbert Schneider（ETH Zurich）
“Deep drug design: Advancing from hits to leads“
Assoc. Prof. Tomoyuki Miyao（NAIST）
“QSPR modeling approaches representing conformations“
Prof. Thierry Langer（University of Vienna）
“Next Generation Pharmacophore Modeling: Novel Concepts & Tools for Molecular Design“
Prof. Alexandre Varnek（University of Strasbourg）
“Artificial Intelligence: The Future for Synthetic Chemistry?“
Prof. Kenji Hori（TS Technology）
“Current in the data-driven synthesis route development methods in TS technology (DSRDM in TST) and its applications for fine chemicals“
Prof. Jose L Medina-Franco（National Autonomous University of Mexico）
“D-Tools: An Open Platform for Research and education in Chemoinformatics.“
Prof. Dragos Horvath（University of Strasbourg）
“Chemography – from Abstract Mathematics to Library Design“
Prof. Shigetaka Tomiya（NAIST）
“Metrology informatics for electron microscopy“
Prof. Hanoch Senderowitz（Bar-Ilan University）
“Materials Informatics for green energy harvesting and storage“
Prof. Mikiya Fujii（NAIST）
“Inorganic Materials Design Utilizing Machine Learning and Generative Adversarial Networks“
Prof. Manabu Sugimoto（Kumamoto University）
“Extended Molecular Representations for Electronic-Structure Informatics and Their Applications“
一般口頭発表者（プログラム順）
田中英也 (NAIST)
“Quantitative structure–reactivity relationship-guided mechanistic study of nitroxyl radical-catalyzed alcohol oxidation“
岩﨑 悠人 (NAIST)
“Rapid evaluation of virtually synthesized compounds using a support vector machine model with reactant-wise kernels“
松清優樹 (名古屋大)
“Omics-based chemical structure generation considering molecular properties via deep reinforcement learning“
Kowit Hengphasatporn (筑波大学)
“The Full Mechanistic Tale of Pralidoxime in Acetylcholinesterase: Binding, Reaction, and Release“
Pavel SIdorov (北海道大学・ICReDD)
“Bridging the Gap: Collaborative Tools for Chemoinformatics and Experimental Chemistry“
Galymzhan Moldagulov (Institute for Basic Science, CARS, UNIST)
“Predicting Ligand-to-Metal Coordination Modes by a Combination of Coordination Templates and Machine Learning“
ポスター発表者（発表順）
P-1 竹内孝輔 (第一三共株式会社)
“Development and Enhancement of NITER: Expanding Access to Multi-Billion-Scale Compound Libraries and Public Data Sources“
P-2 高原渉 (NAIST)
“Domain Adaptation of Local LLMs for Metal-Sulfide Photocatalyst Discovery“
P-3 Sakthivel Balasubramaniyan (Hokkaido University)
“Machine Learning-Driven Retention Time Prediction for High-Throughput Evaluation of Supercritical Chromatography Columns“
P-4 Said Byadi (Hokkaido University)
“Photoswitchable Wnt Pathway Agonists: Molecular Docking and Dynamics Reveal Selective Binding of cis-Isomer to Frizzled Receptors“
P-5 Philippe Gantzer (Hokkaido University)
“Multicomponent Reaction Optimization with Gaussian Processes on Fragment Count Descriptors“
P-6 Kaveri Prasad (Hokkaido University)
“Multicomponent Reaction Optimization with Gaussian Processes on Fragment Count Descriptors“
P-7 Chiharu Konda (OpenEye, Cadence Molecular Sciences)
“Extreme-Scale Search…when Billions aren’t Enough“
P-8 前田陸 (九州工業大学)
“Analysis of factors contributing to uncertainty in BCF predictions for chemical substances“
P-9 坂口大門 (横浜国立大学)
“Analysis of Asymmetric Reduction of Ketones Using Three-Dimensional Electronic States“
P-10 高下大貴 (新潟大学)
“Enhancing Generalization Performance of Molecular Property Prediction via Graph Latent Diffusion Autoencoder“
P-11 Viejay Ordillo (NAIST)
“Generative Modeling for Materials Design and Discovery using Invertible String-based Materials Representation“
P-12 MARTIN (Hokkaido University)
“Developing Embedding Models for Cytochrome P450–Ligand Interaction Scoring“
P-13 杉田陽彩 (NAIST)
“Selective High-Precision Control of Process Variables in Automated Experimentation“
P-14 新川主安 (NAIST)
“Data assimilation model combined with symbolic regression for predicting band gaps of perovskite photocatalytic compounds.“
P-15 水上昌勇 (NAIST)
“Photocatalyst process informatics integrating experiment, simulation, and machine learning“
P-16 Tang Xingyu (Hokkaido University)
“Accelerating efficient reaction path search using NNP-AFIR method by pre-trained models“
P-17 Ruben STAUB (Hokkaido University)
“Solving the Passerini Reaction Controversy with Accelerated Reaction Path Search“
P-18 山田大夢 (NAIST)
“Optimization of Copolymerization Conditions for Novel Copolymers Using Existing Polymerization Data and Physical Information“
P-19 Mayumi Puspita (NAIST)
“Distance-based applicability domain for screening Cu-based tantalate materials for visible-light-responsive photocatalyst candidates“
P-20 松元遊人 (横浜国立大学大学院)
“Fingerprint-Informed Doc2Vec for Activity Prediction and Interpretation“
P-21 義則史弥 (NAIST)
“Predicting the performance of doped hematite photoanodes incorporating the effects of lattice vibrations“
P-22 松尾勇二郎 (株式会社TSテクノロジー)
“Machine learning model for activation free energy and TS geometry of pericyclic reactions“
P-23 山本富也 (NAIST)
“Evaluation Framework for Thermodynamic and Chemical Validity in Generative Composition Models“
P-24 山口徹 (株式会社TSテクノロジー)
“User-Friendly Cloud System for Functional Chemical Synthesis Route Development“
P-25 渡辺航也 (NAIST)
“Development of an XRD Spectrum Generation Model for Crystal Structure Prediction Supporting Multi-site Substitution“
P-26 Milo Roucairol (Hokkaido University)
“Improving Retrosynthetic Planning With New Algorithms“
P-27 Supaporn Klabklaydee (Hokkaido University)
“Breaking the CRAM Behavior: AI-Generated Molecules Unlock Hidden Enzymatic Pathways in Marine Carbon Cycling“
P-28 Addie Jordon (Bielefeld University)
“Optimal Yield Pathways in Complex Reaction Networks“
P-29 Yusuke Tateishi (Kumamoto University)
“Towards Interpretable Prediction of SGLT2 Inhibitor Activity via Flexibility- and Electronic-Structure-Enhanced Graph Neural Networks“
