Author

L. Whittaker

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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Biochemistry· 1 Evolutionary Biology· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Assay:proteomics· 2 Organism:virus· 2 Approach:Bayesian inference· 1 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Research Focus:protein folding & dynamics· 1

Frequent Co-Authors

J. W. McCauley· 2 shared R. S. Daniels· 2 shared A. J. Hay· 1 shared B. Dhayalan· 1 shared B. Ermetal· 1 shared D. E. Wentworth· 1 shared D. Husmeier· 1 shared F. Ismail-Beigi· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersMicrobiology

J. W. McCauley

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Stabilization of a Protein by a Single Halogen-Based Aromatic Amplifier

K. E. Hage, N. B. Phillips, Y.-S. Chen, B. Dhayalan, J. Whittaker, K. Carr, L. Whittaker, M. H. Phillips, F. Ismail-Beigi, M. Meuwly, M. A. Weiss

This study demonstrates that halogenation of an aromatic ring in insulin stabilizes the protein and enhances its resistance to fibrillation and biological activity.

bioRxiv · Jul 25, 2022Biochemistry

A Bayesian approach to incorporate structural data into the mapping of genotype to antigenic phenotype of influenza A(H3N2) viruses

W. T. Harvey, V. Davies, R. S. Daniels, L. Whittaker, V. Gregory, A. J. Hay, D. Husmeier, J. W. McCauley, R. Reeve

This paper uses a Bayesian model to identify genetic changes in influenza A(H3N2) viruses that drive antigenic drift by incorporating protein structural data to improve variable selection accuracy.

bioRxiv · Mar 26, 2022Microbiology

Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution

J. Huddleston, J. R. Barnes, T. Rowe, R. Kondor, D. E. Wentworth, L. Whittaker, B. Ermetal, R. S. Daniels, J. W. McCauley, S. Fujisaki, K. Nakamura, N. Kishida, S. Watanabe, H. Hasegawa, I. Barr, , T. Bedford

This study develops a forecasting framework for influenza A/H3N2 evolution by integrating phenotypic antigenic drift data with sequence-based fitness estimates, showing improved long-term predictions.

bioRxiv · Jun 12, 2020Evolutionary Biology