Author

Alison Hinton

The University of Queensland

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Organism:bacteria (other)· 1 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Assay:protein sequence· 1

Frequent Co-Authors

Amber N. LeeiD· 1 shared Andrew B. DippeliD· 1 shared Angela M. KavanaghiD· 1 shared Bismark AmofahiD· 1 shared Chacko Chakiath· 1 shared Federico DevalleiD· 1 shared Gabrielle J. Lowe· 1 shared Gilad KaplaniD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperBioinformatics

Amber N. LeeORCID

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Author profile →

2 papers

Recent·Most cited

Optimisation of Solid-Phase Antimicrobial Susceptibility Testing for Hydrophobic Antibiotics Using an Agarose-Based MIC Assay

Angela M. Kavanagh, Soumya Ramu, Gabrielle J. Lowe, Alison Hinton, Mark A. T. Blaskovich

The paper develops an agarose-based MIC assay to improve the accuracy of antimicrobial susceptibility testing for hydrophobic antibiotics.

bioRxiv · Jul 28, 2026 · PreprintMicrobiology

Predicting Antibody Self-Association with Sequence Structure Fusion Models: The Central Role of CSI-BLI in Early Developability Screening

Shafayat Ahmed, Federico Devalle, Lauren Leisen, Tony Pham, Bismark Amofah, Amber N. Lee, Mark Hutchinson, Chacko Chakiath, Jen DiChiara, Sharfa Farzandh, Madi Kreitz, Alison Hinton, Neil Mody, Andrew B. Dippel, Gilad Kaplan, Maryam Pouryahya

The paper develops a sequence-structure fusion model to predict antibody self-association using CSI-BLI data, achieving high performance in distinguishing high and low self-interacting clones.

mAbs · Jul 8, 2026Peer-reviewedBioinformatics