Author

Payel Das

IBM (United States)ORCID 0000-0002-7288-0516Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Payel Das1 paper

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Research Focus:benchmarking· 1 Approach:diffusion model· 1 Approach:machine learning (classical)· 1 Assay:protein structure· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Charlotte Mary DeaneiD· 2 shared Lucy VostiD· 2 shared Vijil ChenthamarakshaniD· 2 shared Anna CarberyiD· 1 shared F. von DelftiD· 1 shared Harold GrosjeaniD· 1 shared Jack ScantleburyiD· 1 shared Nathan BrowniD· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Charlotte Mary DeaneORCID

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2 papers

Recent·Most cited

Improving Structural Plausibility in 3D Molecule Generation via Property-Conditioned Training with Distorted Molecules

Lucy Vost, Vijil Chenthamarakshan, Payel Das, Charlotte Mary Deane

The paper improves 3D molecule generation by conditioning diffusion models on distorted molecules to enhance structural plausibility and validity.

bioRxiv · Sep 17, 2024 · PreprintBioinformatics

A Step Towards Generalisability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening

Jack Scantlebury, Lucy Vost, Anna Carbery, Thomas E. Hadfield, Oliver M. Turnbull, Nathan Brown, Vijil Chenthamarakshan, Payel Das, Harold Grosjean, F. von Delft, Charlotte Mary Deane

The paper develops a machine learning scoring function for virtual screening that avoids dataset biases and demonstrates its ability to identify important binding interactions through input attribution.

bioRxiv · Oct 28, 2022 · PreprintBioinformatics