Publications by authors named "Kimito Funatsu"

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An Attempt to Classify Elementary Reactions on the Basis of TS Motifs.
Kenji Hori, Yujiro Matsuo, Toru Yamaguchi, Kimito Funatsu

Mol Inform· February 2025

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Correction to "Designing Heat-Resistant and Moldable Polyester Resin by the Integration of Machine Learning Models with Expert Knowledge".
Fan Zhang, Tomoyuki Miyao, Yuuta Izumiya, Chia Hsiu Chen, Kimito Funatsu

ACS Appl Polym Mater· February 2025

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Octanol/water partition coefficients estimated using retention times in reverse-phase liquid chromatography and calculated in silico as one of the determinant factors for pharmacokinetic parameter estimations of general chemical substances.
Koichiro Adachi, Makiko Shimizu, Fumiaki Shono, Kimito Funatsu, Hiroshi Yamazaki

J Toxicol Sci· April 2024

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Screening and Validation of Odorants against Influenza A Virus Using Interpretable Regression Models.
Swarit Jasial, Jieying Hu, Tomoyuki Miyao, Yui Hirama, Shintaro Onishi, Kimito Funatsu

ACS Pharmacol Transl Sci· January 2023

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Correction to "An Updated Prediction Method for Volumes of Systemic Circulation of 323 Disparate Chemicals for Use in Physiologically Based Pharmacokinetic Models to Estimate Plasma and Tissue Concentrations after Oral Doses in Rats".
Yusuke Kamiya, Kentaro Handa, Tomonori Miura, Junya Ohori, Makiko Shimizu, Kimito Funatsu

Chem Res Toxicol· August 2022

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Technique of Augmenting Molecular Graph Data by Perturbating Hidden Features.
Takahiro Inoue, Kenichi Tanaka, Kimito Funatsu

Mol Inform· July 2022

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Prediction of Reaction Yield for Buchwald-Hartwig Cross-coupling Reactions Using Deep Learning.
Akinori Sato, Tomoyuki Miyao, Kimito Funatsu

Mol Inform· February 2022

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Prediction of permeability across intestinal cell monolayers for 219 disparate chemicals using in vitro experimental coefficients in a pH gradient system and in silico analyses by trivariate linear regressions and machine learning.
Yusuke Kamiya, Asuka Omura, Riku Hayasaka, Rie Saito, Izumi Sano, Kimito Funatsu

Biochem Pharmacol· October 2021

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An Updated Prediction Method for Volumes of Systemic Circulation of 323 Disparate Chemicals for Use in Physiologically Based Pharmacokinetic Models to Estimate Plasma and Tissue Concentrations after Oral Doses in Rats.
Yusuke Kamiya, Kentaro Handa, Tomonori Miura, Junya Ohori, Makiko Shimizu, Kimito Funatsu

Chem Res Toxicol· October 2021

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Interpretation of Ligand-Based Activity Cliff Prediction Models Using the Matched Molecular Pair Kernel.
Shunsuke Tamura, Swarit Jasial, Tomoyuki Miyao, Kimito Funatsu

Molecules· August 2021

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Sparse Topological Pharmacophore Graphs for Interpretable Scaffold Hopping.
Hiroshi Nakano, Tomoyuki Miyao, Jasial Swarit, Kimito Funatsu

J Chem Inf Model· July 2021

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Ranking-Oriented Quantitative Structure-Activity Relationship Modeling Combined with Assay-Wise Data Integration.
Katsuhisa Matsumoto, Tomoyuki Miyao, Kimito Funatsu

ACS Omega· May 2021

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Improvement of the Structure Generator DAECS with Respect to Structural Diversity.
Takahiro Inoue, Kenichi Tanaka, Masaaki Kotera, Kimito Funatsu

Mol Inform· April 2021

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Comparing predictive ability of QSAR/QSPR models using 2D and 3D molecular representations.
Akinori Sato, Tomoyuki Miyao, Swarit Jasial, Kimito Funatsu

J Comput Aided Mol Des· February 2021

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Prediction of Input Parameters for Simplified Physiologically Based Pharmacokinetic Models for Estimating Plasma, Liver, and Kidney Exposures in Rats after Oral Doses of 246 Disparate Chemicals.
Yusuke Kamiya, Kentaro Handa, Tomonori Miura, Mayu Yanagi, Kazuki Shigeta, Kimito Funatsu

Chem Res Toxicol· February 2021

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Investigation of Preprocessing and Validation Methodologies for PAT: Case Study of the Granulation and Coating Steps for the Manufacturing of Ethenzamide Tablets.
Shojiro Shibayama, Kimito Funatsu

AAPS PharmSciTech· January 2021

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Ligand-based Activity Cliff Prediction Models with Applicability Domain.
Shunsuke Tamura, Tomoyuki Miyao, Kimito Funatsu

Mol Inform· December 2020

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Physiologically Based Pharmacokinetic Models Predicting Renal and Hepatic Concentrations of Industrial Chemicals after Virtual Oral Doses in Rats.
Yusuke Kamiya, Shohei Otsuka, Tomonori Miura, Manae Yoshizawa, Ayane Nakano, Kimito Funatsu

Chem Res Toxicol· July 2020

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Application of the mol2vec Technology to Large-size Data Visualization and Analysis.
Shojiro Shibayama, Gilles Marcou, Dragos Horvath, Igor I Baskin, Kimito Funatsu

Mol Inform· June 2020

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Rethinking drug design in the artificial intelligence era.
Petra Schneider, W Patrick Walters, Alleyn T Plowright, Norman Sieroka, Jennifer Listgarten, Kimito Funatsu

Nat Rev Drug Discov· May 2020

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Exploring Topological Pharmacophore Graphs for Scaffold Hopping.
Hiroshi Nakano, Tomoyuki Miyao, Kimito Funatsu

J Chem Inf Model· April 2020

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Comparison and improvement of the predictability and interpretability with ensemble learning models in QSPR applications.
Chia-Hsiu Chen, Kenichi Tanaka, Masaaki Kotera, Kimito Funatsu

J Cheminform· March 2020

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Determination and prediction of permeability across intestinal epithelial cell monolayer of a diverse range of industrial chemicals/drugs for estimation of oral absorption as a putative marker of hepatotoxicity.
Yusuke Kamiya, Hiroka Takaku, Rio Yamada, Chisato Akase, Yuto Abe, Kimito Funatsu

Toxicol Rep· January 2020

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Metabolic disassembler for understanding and predicting the biosynthetic units of natural products.
Kohei Amano, Tsubasa Matsumoto, Kenichi Tanaka, Kimito Funatsu, Masaaki Kotera

BMC Bioinformatics· December 2019

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Evaluation of different virtual screening strategies on the basis of compound sets with characteristic core distributions and dissimilarity relationships.
Tomoyuki Miyao, Swarit Jasial, Jürgen Bajorath, Kimito Funatsu

J Comput Aided Mol Des· August 2019

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