World's Best Scientists 2026 revealed!
Kimito Funatsu

Kimito Funatsu

D-Index & Metrics

Computer Science

D-Index
40
Citations
8633
World Ranking
9166
National Ranking
127

Overview

Kimito Funatsu is affiliated with the University of Tokyo in Japan and has contributed extensively to research in computational methods applied to chemistry and pharmacology. Their publication record includes significant work on computational drug discovery methods, machine learning applications in materials science, and analytical chemistry techniques.

The main fields of study in Funatsu's work are Computer Science and Chemistry, with a particular focus on subfields such as Computational Theory and Mathematics, Materials Chemistry, Spectroscopy, Molecular Biology, and Pharmacology.

Funatsu's research topics cover a range of areas including:

  • Computational Drug Discovery Methods
  • Machine Learning in Materials Science
  • Analytical Chemistry and Chromatography
  • Carcinogens and Genotoxicity Assessment
  • Drug Transport and Resistance Mechanisms
  • Pharmacogenetics and Drug Metabolism
  • Analytical Methods in Pharmaceuticals

Frequent publication venues for their work include:

  • Molecular Informatics
  • Chemical Research in Toxicology
  • Advanced Materials Interfaces
  • Journal of Chemical Information and Modeling
  • ACS Applied Polymer Materials

Co-authorship has been a notable aspect of their career, with several frequent collaborators such as:

  • Tomoyuki Miyao
  • Fumiaki Shono
  • Hiroshi Yamazaki
  • Yusuke Kamiya
  • Makiko Shimizu

Recent publications reflect a focus on predictive modeling and permeability studies related to pharmacokinetics and toxicology. Notable papers include:

  • "Comparison and improvement of the predictability and interpretability with ensemble learning models in QSPR applications" (2020, Journal of Cheminformatics)
  • "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" (2020, Toxicology Reports)
  • "In Silico 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" (2021, Chemical Research in Toxicology)
  • "Physiologically Based Pharmacokinetic Models Predicting Renal and Hepatic Concentrations of Industrial Chemicals after Virtual Oral Doses in Rats" (2020, Chemical Research in Toxicology)
  • "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" (2021, Biochemical Pharmacology)

Best Publications

  • MassBank: a public repository for sharing mass spectral data for life sciences.

    Hisayuki Horai;Masanori Arita;Masanori Arita;Shigehiko Kanaya;Yoshito Nihei

  • Rethinking drug design in the artificial intelligence era

    Petra Schneider;W. Patrick Walters;Alleyn T. Plowright;Norman Sieroka

  • GA strategy for variable selection in QSAR studies: GA-based PLS analysis of calcium channel antagonists.

    Kiyoshi Hasegawa;Yoshikatsu Miyashita;Kimito Funatsu

  • Development of a new soft sensor method using independent component analysis and partial least squares

    Hiromasa Kaneko;Masamoto Arakawa;Kimito Funatsu

  • Genetic algorithm-based wavelength selection method for spectral calibration

    Masamoto Arakawa;Yosuke Yamashita;Kimito Funatsu

  • SOPHIA, A KNOWLEDGE BASE-GUIDED REACTION PREDICTION SYSTEM-UTILIZATION OF A KNOWLEDGE BASE DERIVED FROM A REACTION DATABASE

    Hiroko Satoh;Kimito Funatsu

  • Adaptive soft sensor based on online support vector regression and Bayesian ensemble learning for various states in chemical plants

    Hiromasa Kaneko;Kimito Funatsu

  • Inverse QSPR/QSAR Analysis for Chemical Structure Generation (from y to x).

    Tomoyuki Miyao;Hiromasa Kaneko;Kimito Funatsu

  • Further development of structure generation in the automated structure elucidation system CHEMICS

    Kimito Funatsu;Nobuyoshi Miyabayashi;Shin-ichi Sasaki

  • GA strategy for variable selection in QSAR studies: application of GA-based region selection to a 3D-QSAR study of acetylcholinesterase inhibitors.

    Kiyoshi Hasegawa;Toshiro Kimura;Kimito Funatsu

  • Application of Online Support Vector Regression for Soft Sensors

    Hiromasa Kaneko;Kimito Funatsu

  • Feature selection by genetic algorithms for mass spectral classifiers

    H Yoshida;R Leardi;K Funatsu;K Varmuza

  • Maintenance-free soft sensor models with time difference of process variables

    Hiromasa Kaneko;Kimito Funatsu

  • Fast optimization of hyperparameters for support vector regression models with highly predictive ability

    Hiromasa Kaneko;Kimito Funatsu

  • Classification of the Degradation of Soft Sensor Models and Discussion on Adaptive Models

    Hiromasa Kaneko;Kimito Funatsu

  • A NOVEL APPROACH TO RETROSYNTHETIC ANALYSIS USING KNOWLEDGE BASES DERIVED FROM REACTION DATABASES

    Koji Satoh;Kimito Funatsu

  • Recent Advances in the Automated Structure Elucidation System, CHEMICS. Utilization of Two-Dimensional NMR Spectral Information and Development of Peripheral Functions for Examination of Candidates

    Kimito Funatsu;Shin-ichi Sasaki

  • GA Strategy for Variable Selection in QSAR Studies: Enhancement of Comparative Molecular Binding Energy Analysis by GA‐Based PLS Method

    Kiyoshi Hasegawa;Toshiro Kimura;Kimito Funatsu

  • GA Strategy for Variable Selection in QSAR Studies: GA-Based Region Selection for CoMFA Modeling

    Toshiro Kimura;Kiyoshi Hasegawa;Kimito Funatsu

  • Development of Soft Sensor Models Based on Time Difference of Process Variables with Accounting for Nonlinear Relationship

    Hiromasa Kaneko;Kimito Funatsu

Frequent Co-Authors

Jürgen Bajorath
Jürgen Bajorath University of Bonn
Takaaki Nishioka
Takaaki Nishioka Kyoto University
Takayuki Tohge
Takayuki Tohge Nara Institute of Science and Technology
Ryo Taguchi
Ryo Taguchi University of Tokyo
Fumio Matsuda
Fumio Matsuda Osaka University
Shigehiko Kanaya
Shigehiko Kanaya Nara Institute of Science and Technology
Yoshiya Oda
Yoshiya Oda Eisai (Japan)
Daisuke Shibata
Daisuke Shibata Kyoto University
Tsuyoshi Kawai
Tsuyoshi Kawai Nara Institute of Science and Technology

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