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  • Amesformer: a graph transformer neural network for mutagenicity prediction

    Luke Thompson, Josiah Evans, Slade Matthews

    ChemRxiv (2024), doi:10.26434/chemrxiv-2024-sjrb4-v2
  • Low-cost quantum mechanical descriptors for data efficient skin sensitization QSAR models

    Davy Guan, Raymond Lui, Slade Matthews

    Current Research in Toxicology 7: 100183 (2024)
  • Deus Ex Machina? The Rise of Artificial Intelligence in Toxicology

    Raymond Lui

    Chemical Research in Toxicology 37: 525-527 (2024)
  • Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project

    Ayako Furuhama, Airi Kitazawa, J Yao, Carlos E Matos dos Santos, James Rathman, Chihae Yang, J Vinícius Ribeiro, Kevin Cross, Glen Myatt, Giuseppa Raitano, Emilio Benfenati, Nina Jeliazkova, Roustem Saiakhov, Suman Chakravarti, Robert S Foster, Cecilia Bossa, C Laura Battistelli, Romualdo Benigni, Toshihiko Sawada, Hiroaki Wasada, Tomohiro Hashimoto, Menghua Wu, Regina Barzilay, Pankaj R Daga, Robert D Clark, Jordi Mestres, Aaron Montero, Elisabet Gregori-Puigjané, Petko Petkov, Hristiana Ivanova, Ovanes Mekenyan, Slade Matthews, Davy Guan, John Spicer, Raymond Lui, Yoshihiro Uesawa, Koti Kurosaki, Yasunari Matsuzaka, S Sasaki, Mark TD Cronin, Sam J Belfield, James W Firman, Nicoleta Spînu, M Qiu, JM Keca, Giuseppina Gini, Ting Li, Weida Tong, Huixiao Hong, Zhichao Liu, Yoshinobu Igarashi, Hiroshi Yamada, Kei-ichi Sugiyama, Masamitsu Honma

    SAR and QSAR in Environmental Research 34: 983-1001 (2023)
  • Mechanistic Task Groupings Enhance Multitask Deep Learning of Strain-Specific Ames Mutagenicity

    Raymond Lui, Davy Guan, Slade Matthews

    Chemical Research in Toxicology 36: 1248-1254 (2023)
  • Multiple Instance Learning Improves Ames Mutagenicity Prediction for Problematic Molecular Species

    Samuel V Feeney, Raymond Lui, Davy Guan, Slade Matthews

    Chemical Research in Toxicology 36: 1227-1237 (2023)
  • An Open Drug Discovery Competition: Experimental Validation of Predictive Models in a Series of Novel Antimalarials

    Edwin Tse, Laksh Aithani, Mark Anderson, Jonathan Cardoso-Silva, Giovanni Cincilla, Gareth J Conduit, Mykola Galushka, Davy Guan, Irene Hallyburton, Benedict WJ Irwin, Kiaran Kirk, Adele M Lehane, Julia Lindblom, Raymond Lui, Slade Matthews, James McCulloch, Alice Motion, Ho Leung Ng, Mario Öeren, Murray N Robertson, Vito Spadavecchio, Vasileios Tatsis, Willem P van Hoorn, Alexander Wade, Thomas M Whitehead, Paul Willis, Matthew Todd

    Journal of Medicinal Chemistry 64: 16450-16463 (2021)
  • A comparison of molecular representations for lipophilicity quantitative structure–property relationships with results from the SAMPL6 LogP Prediction Challenge

    Raymond Lui, Davy Guan, Slade Matthews

    Journal of Computer-Aided Molecular Design 34: 523-534 (2020)
  • LogP prediction performance with the SMD solvation model and the M06 density functional family for SAMPL6 Blind Prediction Challenge molecules

    Davy Guan, Raymond Lui, Slade Matthews

    Journal of Computer-Aided Molecular Design 34: 511-522 (2020)
  • QSAR ligand dataset for modelling mutagenicity, genotoxicity, and rodent carcinogenicity

    Davy Guan, Kevin Fan, Ian Spence, Slade Matthews

    Data in Brief 17: 876-884 (2018)
  • Combining machine learning models of in vitro and in vivo bioassays improves rat carcinogenicity prediction

    Davy Guan, Kevin Fan, Ian Spence, Slade Matthews

    Regulatory Toxicology and Pharmacology 94: 8-15 (2018)
  • Diagnosis of oligodendroglioma: Molecular and classical histological assessment in the twenty-first century

    Slade Matthews, Peter Succar, Herbert Jelinek, Brent McParland, Michael Buckland, Craig S McLachlan

    Asia-Pacific Journal of Clinical Oncology 8: 213-216 (2012)
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