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Matthew Segall

optibrium ltd., f10-13 blenheim house, cambridge innovation park, denny end road, cambridge cb25 9gl, u.k.

30H指数
97论文数
3.0W被引数
收录论文 33
发表时间
Comparing massively-multitask regression algorithms for drug discovery比较大规模多任务回归算法在药物发现中的应用
err2026-02-05
err0
PREAI
errEric J. Martin; Xiang-Wei Zhu; Patrick Riley; Steven Kearnes; Ekaterina A. Sosnina; Li Tian; Chi-Ming Che; Zijian Wang; Ying Wei; Thomas M. Whitehead; Gareth J. Conduit; Matthew D. Segall
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Predicting Regioselectivity of Cytosolic Sulfotransferase Metabolism for Drugs
err2023-05-25
err4
PREAI
errÖeren, Mario; Kaempf, Sylvia C.; Ponting, David J.; Hunt, Peter A.; Segall, Matthew D.
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Predicting Regioselectivity of AO, CYP, FMO, and UGT Metabolism Using Quantum Mechanical Simulations and Machine Learning
err2022-10-14
err11
PREAI
errOeren, Mario; Walton, Peter J.; Suri, James; Ponting, David J.; Hunt, Peter A.; Segall, Matthew D.
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Imputation of sensory properties using deep learning
err2021-10-30
err6
PREAI
errMahmoud, Samar; Irwin, Benedict; Chekmarev, Dmitriy; Vyas, Shyam; Kattas, Jeff; Whitehead, Thomas; Mansley, Tamsin; Bikker, Jack; Conduit, Gareth; Segall, Matthew
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Predicting reactivity to drug metabolism: beyond P450s-modelling FMOs and UGTs
err2020-06-12
err13
PREAI
errOeren, Mario; Walton, Peter J.; Hunt, Peter A.; Ponting, David J.; Segall, Matthew D.
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Practical Applications of Deep Learning To Impute Heterogeneous Drug Discovery Data
err2020-06-01
err35
PREAI
errIrwin, Benedict W. J.; Levell, Julian R.; Whitehead, Thomas M.; Segall, Matthew D.; Conduit, Gareth J.
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Advances in the study of drug metabolism - symposium report of the 12th Meeting of the International Society for the Study of Xenobiotics (ISSX)
err2020-05-26
err7
errOAAI
errRussell, Laura E.; Schleiff, Mary Alexandra; Gonzalez, Eric; Bart, Aaron G.; Broccatelli, Fabio; Hartman, Jessica H.; Humphreys, W. Griffith; Lauschke, Volker M.; Martin, Iain; Nwabufo, Chukwunonso; Prasad, Bhagwat; Scott, Emily E.; Segall, Matthew; Takahashi, Ryan; Taub, Mitchell E.; Sodhi, Jasleen K.
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Predicting pKa Using a Combination of Semi-Empirical Quantum Mechanics and Radial Basis Function Methods
err2020-05-01
err25
PREAI
errHunt, Peter; Hosseini-Gerami, Layla; Chrien, Tomas; Plante, Jeffrey; Ponting, David J.; Segall, Matthew
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Capturing and applying knowledge to guide compound optimisation
err2019-05-01
err4
PREAI
errSegall, Matthew; Mansley, Tamsin; Hunt, Peter; Champness, Edmund
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Imputation of Assay Bioactivity Data Using Deep Learning
err2019-02-12
err41
errOAAI
errWhitehead, T. M.; Irwin, B. W. J.; Hunt, P.; Segall, M. D.; Conduit, G. J.
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A model-based assay design to reproduce in vivo patterns of acute drug-induced toxicity
err2017-08-29
err18
errOAAI
errKuepfer, Lars; Clayton, Olivia; Thiel, Christoph; Cordes, Henrik; Nudischer, Ramona; Blank, Lars M.; Baier, Vanessa; Heymans, Stephane; Caiment, Florian; Roth, Adrian; Fluri, David A.; Kelm, Jens M.; Castell, Jose; Selevsek, Nathalie; Schlapbach, Ralph; Keun, Hector; Hynes, James; Sarkans, Ugis; Gmuender, Hans; Herwig, Ralf; Niederer, Steven; Schuchhardt, Johannes; Segall, Matthew; Kleinjans, Jos
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Avoiding Missed Opportunities by Analyzing the Sensitivity of Our Decisions
err2016-03-18
err19
PREAI
errSegall, Matthew D.; Yusof, Iskander; Champness, Edmund J.
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Breaking free from chemical spreadsheets
err2015-09-01
err5
PREAI
errSegall, Matthew; Champness, Ed; Leeding, Chris; Chisholm, James; Hunt, Peter; Elliott, Alex; Garcia-Martinez, Hector; Foster, Nick; Dowling, Samuel
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