Author

Timothy E. H. Allen

ORCID 0000-0001-7369-0901Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Rabia T. Khan· 2 shared Anil VasudevaniD· 1 shared Carson J. BryantiD· 1 shared Danny IncarnatoiD· 1 shared James L. McDonaghiD· 1 shared Malgorzata BronceliD· 1 shared Maurinne BonnetiD· 1 shared Susan M. Boyd· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 18 mutual co-author links

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2 shared papersBioinformatics

Rabia T. Khan

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2 papers

Recent·Most cited

BioinformaticsComputational and Structural Biotechnology JournalPeer-reviewedMar 1, 2026

Generative Chemistry Platform for Small Molecules Targeting RNA: A Case Study for Chemical Optimization

Timothy E. H. Allen, Susan M. Boyd, Maurinne Bonnet, Rabia T. Khan

The paper introduces a generative chemistry platform for designing RNA-targeting small molecules and compares its performance to existing models and human-designed chemistry.

DOI 10.34133/csbj.0218

deep learningmachine learning (classical)

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BioinformaticsbioRxivPreprintJan 31, 2024

Physicochemical Principles Driving Small Molecule Binding to RNA

Timothy E. H. Allen, James L. McDonagh, Malgorzata Broncel…·Rabia T. Khan

The paper derives physicochemical rules for small molecule binding to RNA using extensive binding data and applies them to validate known RNA-targeting compounds and drugs.

10 citations

statistical model

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