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Organic Chemistry

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Predictive Minisci and P450 Late Stage Functionalization with Transfer Learning

Emma King-Smith, Felix A. Faber, Usa Reilly, Anton V. Sinitskiy, Qingyi Yang, Bo Liu, Dennis Hyek, Alpha A. Lee

Version 3 posted 06 September 2023

1,057

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Theoretical and Computational Chemistry

Working Paper

CACHE (Critical Assessment of Computational Hit-finding Experiments): A public-private partnership benchmarking initiative to enable the development of computational methods for hit-finding

Suzanne Ackloo, Rima Al-awar, Rommie E. Amaro, Cheryl H. Arrowsmith, Hatylas Azevedo, Robert A. Batey, Yoshua Bengio, Ulrich A.K. Betz, Cristian G. Bologa, John D. Chodera, Wendy D. Cornell, Ian Dunham, Gerhard F. Ecker, Kristina Edfeldt, Aled M. Edwards, Michael K. Gilson, Claudia R. Gordijo, Gerhard Hessler, Alexander Hillisch, Anders Hogner, John J. Irwin, Johanna M. Jansen, Daniel Kuhn, Andrew R. Leach, Alpha A. Lee, Uta Lessel, John Moult, Ingo Muegge, Tudor I. Oprea, Benjamin G. Perry, Patrick Riley, Kumar Singh Saikatendu, Vijayaratnam Santhakumar, Matthieu Schapira, Cora Scholten, Matthew H. Todd, Masoud Vedadi, Andrea Volkamer, Timothy M. Willson

Version 1 posted 22 October 2021

2,220

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Theoretical and Computational Chemistry

Working Paper

CoPriNet: Graph Neural Networks provide accurate and rapid compound price prediction for molecule prioritisation.

Ruben Sanchez-Garcia, Dávid Havasi, Gergely Takács, Matthew C. Robinson, Alpha Lee, Frank von Delft, Charlotte M. Deane

Version 6 posted 31 October 2022

1,132

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Organic Chemistry

Working Paper

Probing the Chemical "Reactome" with High Throughput Experimentation Data

Emma King-Smith, Simon Berritt, Louise Bernier, Xinjun Hou, Jacquelyn Klug-McLeod, Jason Mustakis, Neal Sach, Joseph Tucker, Qingyi Yang, Roger Howard, Alpha Lee

Version 2 posted 06 September 2023

1,259

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Energy

Working Paper

Impedance-based forecasting of battery performance amid uneven usage

Penelope Jones, Ulrich Stimming, Alpha Lee

Version 1 posted 23 November 2021

776

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1

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Theoretical and Computational Chemistry

Working Paper

Dataset Bias in the Natural Sciences: A Case Study in Chemical Reaction Prediction and Synthesis Design

Ryan-Rhys Griffiths, Philippe Schwaller, Alpha Lee

Version 1 posted 21 November 2018

1,414

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3

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Theoretical and Computational Chemistry

Working Paper

Quantitative Interpretation Explains Machine Learning Models for Chemical Reaction Prediction and Uncovers Bias

David Peter Kovacs, William McCorkindale, Alpha Lee

Version 1 posted 08 October 2020

468

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Theoretical and Computational Chemistry

Working Paper

The Photoswitch Dataset: A Molecular Machine Learning Benchmark for the Advancement of Synthetic Chemistry

Aditya Raymond Thawani, Ryan-Rhys Griffiths, Arian Jamasb, Anthony Bourached, Penelope Jones, William McCorkindale, Alexander Aldrick, Alpha Lee

Version 1 posted 06 July 2020

1,348

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3

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Theoretical and Computational Chemistry

Working Paper

Molecular Transformer – A Model for Uncertainty-Calibrated Chemical Reaction Prediction

Philippe Schwaller, Teodoro Laino, Theophile Gaudin, Peter Bolgar, Costas Bekas, Alpha A. Lee

Version 2 posted 30 May 2019

3,268

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1

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Organic Chemistry

Working Paper

Deconvoluting Low Yield from Weak Potency in Direct-to-Biology Workflows with Machine Learning

William McCorkindale, Mihajlo Filep, Nir London, Alpha A. Lee, Emma King-Smith

Version 2 posted 09 February 2024

387

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11 results in Alpha Lee in Authors: Alpha Lee

Predictive Minisci and P450 Late Stage Functionalization with Transfer Learning

CACHE (Critical Assessment of Computational Hit-finding Experiments): A public-private partnership benchmarking initiative to enable the development of computational methods for hit-finding

CoPriNet: Graph Neural Networks provide accurate and rapid compound price prediction for molecule prioritisation.

Probing the Chemical "Reactome" with High Throughput Experimentation Data

Impedance-based forecasting of battery performance amid uneven usage

Dataset Bias in the Natural Sciences: A Case Study in Chemical Reaction Prediction and Synthesis Design

Quantitative Interpretation Explains Machine Learning Models for Chemical Reaction Prediction and Uncovers Bias

The Photoswitch Dataset: A Molecular Machine Learning Benchmark for the Advancement of Synthetic Chemistry

Molecular Transformer – A Model for Uncertainty-Calibrated Chemical Reaction Prediction

Deconvoluting Low Yield from Weak Potency in Direct-to-Biology Workflows with Machine Learning

11 results in Authors: Alpha Lee