Author

Samiran Sen

Centre National de la Recherche ScientifiqueORCID 0000-0002-1922-7796Unclaimed 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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Approach:Bayesian inference· 2 Assay:protein structure· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Massimiliano BonomiiD· 2 shared Tatiana I. MorozovaiD· 2 shared Vincent SchnapkaiD· 2 shared Samuel HoffiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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2 shared papersBioinformatics

Massimiliano BonomiORCID

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2 papers

Recent·Most cited

BioinformaticsJournal of Chemical Theory and ComputationPeer-reviewedJul 13, 2026

Advancing in silico drug design with Bayesian refinement of AlphaFold models

Samiran Sen, Samuel Hoff, Tatiana I. Morozova…·Massimiliano Bonomi

This paper introduces bAIes, a method that improves AlphaFold2 models using Bayesian inference to enhance virtual screening accuracy for drug discovery.

DOI 10.1021/acs.jctc.6c00868

protein structureBayesian inference

𝕏 PostBluesky

BioinformaticsNature CommunicationsPeer-reviewedFeb 5, 2026

Atomic resolution ensembles of intrinsically disordered proteins with Alphafold

Vincent Schnapka, Tatiana I. Morozova, Samiran Sen, Massimiliano Bonomi

This paper introduces bAIes, a Bayesian framework for generating accurate atomic-resolution ensembles of intrinsically disordered proteins using AlphaFold2 and molecular mechanics, showing improved accuracy over existing methods.

23 citationstop 1%

protein structuredeep learning

𝕏 PostBluesky