Author

Vijil Chenthamarakshan

IBM (United States)ORCID 0000-0001-7830-5777Unclaimed ORCID profile · follow to get notified of new preprints

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 Payel DasiD· 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

BioinformaticsbioRxivPreprintSep 17, 2024

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.

2 citations

diffusion modeldrug response / drug discovery

𝕏 PostBluesky

BioinformaticsbioRxivPreprintOct 28, 2022

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

Jack Scantlebury, Lucy Vost, Anna Carbery…·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.

2 citations

protein structuremachine learning (classical)

𝕏 PostBluesky