Jack Scantlebury

ORCID

Publication Activity (10 Years)

Years Active: 2020-2023
Publications (10 Years): 5

Top Venues

Journal of chemical information and modeling

Google Inc New York

University College London (MSC)

This page only lists publications with an associated author ORCID identifier.

Affiliation History

Google Inc New York Jan 17 2020 - May 15 2020

United States

Software Engineering Intern

Education History

University College London Sep 25 2017 - Aug 31 2018

United Kingdom

MSC :: Physics and Astronomy

Publications

Jack Scantlebury, Lucy Vost, Anna Carbery, Thomas E Hadfield, Oliver M Turnbull, Nathan Brown, Vijil Chenthamarakshan, Payel Das, Harold Grosjean, Frank von Delft, Charlotte M Deane
A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening. Journal of chemical information and modeling 63 (10) (2023)
Jack Scantlebury, Lucy Vost, Anna Carbery, Thomas E Hadfield, Oliver M Turnbull, Nathan Brown, Vijil Chenthamarakshan, Payel Das, Harold Grosjean, Frank von Delft, Charlotte M Deane
A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening. Journal of chemical information and modeling 63 (10) (2023)
Jack Scantlebury, Lucy Vost, Anna Carbery, Thomas E Hadfield, Oliver M Turnbull, Nathan Brown, Vijil Chenthamarakshan, Payel Das, Harold Grosjean, Frank von Delft, Charlotte M Deane
A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening. Journal of chemical information and modeling (2023)
Jack Scantlebury, Lucy Vost, Anna Carbery, Thomas E Hadfield, Oliver M Turnbull, Nathan Brown, Vijil Chenthamarakshan, Payel Das, Harold Grosjean, Frank von Delft, Charlotte M Deane
A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening. Journal of chemical information and modeling (2023)
Jack Scantlebury, Nathan Brown, Frank von Delft, Charlotte M Deane
Data Set Augmentation Allows Deep Learning-Based Virtual Screening to Better Generalize to Unseen Target Classes and Highlight Important Binding Interactions. Journal of chemical information and modeling 60 (8) (2020)

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Publication Activity (10 Years)

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Jack Scantlebury