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Complete Genome Sequences of Vibrio cholerae -Specific Bacteriophages 24 and X29 (2017)
Journal Article
Bhandare, S. G., Warry, A., Emes, R. D., Hooton, S. P., Barrow, P. A., & Atterbury, R. J. (2017). Complete Genome Sequences of Vibrio cholerae -Specific Bacteriophages 24 and X29. Genome Announcements, 5(46), Article e01013. https://doi.org/10.1128/genomeA.01013-17

The complete genomes of two Vibrio cholerae bacteriophages of potential interest for cholera bacteriophage (phage) therapy were sequenced and annotated. The genome size of phage 24 is 44,395 bp encoding 71 putative proteins, and that of phage X29 is... Read More about Complete Genome Sequences of Vibrio cholerae -Specific Bacteriophages 24 and X29.

Next generation interatomic potentials for condensed systems (2014)
Journal Article
Handley, C. M., & Behler, J. (2014). Next generation interatomic potentials for condensed systems. European Physical Journal B: Condensed Matter and Complex Systems, 87(7), https://doi.org/10.1140/epjb/e2014-50070-0

The computer simulation of condensed systems is a challenging task. While electronic structure methods like density-functional theory (DFT) usually provide a good compromise between accuracy and efficiency, they are computationally very demanding and... Read More about Next generation interatomic potentials for condensed systems.

A Multi-Objective Approach to Force Field Optimization: Structures and Spin State Energetics of d6 Fe(II) Complexes (2011)
Journal Article
Handley, C. M., & Deeth, R. J. (2012). A Multi-Objective Approach to Force Field Optimization: Structures and Spin State Energetics of d6 Fe(II) Complexes. Journal of Chemical Theory and Computation, 8(1), 194-202. https://doi.org/10.1021/ct200584a

The next generation of force fields (FFs), regardless of the accuracy of the potential energy representation, will always have parameters that must be fitted in order to reproduce experimental and/or ab initio data accurately. Single objective metho... Read More about A Multi-Objective Approach to Force Field Optimization: Structures and Spin State Energetics of d6 Fe(II) Complexes.

Potential Energy Surfaces Fitted by Artificial Neural Networks (2010)
Journal Article
Handley, C. M., & Popelier, P. L. A. (2010). Potential Energy Surfaces Fitted by Artificial Neural Networks. Journal of Physical Chemistry A, 114(10), 3371-3383. https://doi.org/10.1021/jp9105585

Molecular mechanics is the tool of choice for the modeling of systems that are so large or complex that it is impractical or impossible to model them by ab initio methods. For this reason there is a need for accurate potentials that are able to quick... Read More about Potential Energy Surfaces Fitted by Artificial Neural Networks.

Optimal construction of a fast and accurate polarisable water potential based on multipole moments trained by machine learning (2009)
Journal Article
Handley, C. M., Hawe, G. I., Kell, D. B., & Popelier, P. L. A. (2009). Optimal construction of a fast and accurate polarisable water potential based on multipole moments trained by machine learning. Physical Chemistry Chemical Physics, 11(30), 6365-6376. https://doi.org/10.1039/b905748j

To model liquid water correctly and to reproduce its structural, dynamic and thermodynamic properties warrants models that account accurately for electronic polarisation. We have previously demonstrated that polarisation can be represented by fluctua... Read More about Optimal construction of a fast and accurate polarisable water potential based on multipole moments trained by machine learning.

Dynamically Polarizable Water Potential Based on Multipole Moments Trained by Machine Learning (2009)
Journal Article
Handley, C. M., & Popelier, P. L. A. (2009). Dynamically Polarizable Water Potential Based on Multipole Moments Trained by Machine Learning. Journal of Chemical Theory and Computation, 5(6), 1474-1489. https://doi.org/10.1021/ct800468h

It is widely accepted that correctly accounting for polarization within simulations involving water is critical if the structural, dynamic, and thermodynamic properties of such systems are to be accurately reproduced. We propose a novel potential for... Read More about Dynamically Polarizable Water Potential Based on Multipole Moments Trained by Machine Learning.

Beyond Point Charges: Dynamic Polarization from Neural Net Predicted Multipole Moments (2008)
Journal Article
Darley, M. G., Handley, C. M., & Popelier, P. L. A. (2008). Beyond Point Charges: Dynamic Polarization from Neural Net Predicted Multipole Moments. Journal of Chemical Theory and Computation, 4(9), 1435-1448. https://doi.org/10.1021/ct800166r

Intramolecular polarization is the change to the electron density of a given atom upon variation in the positions of the neighboring atoms. We express the electron density in terms of multipole moments. Using glycine and N-methylacetamide (NMA) as pi... Read More about Beyond Point Charges: Dynamic Polarization from Neural Net Predicted Multipole Moments.

Privacy Preserving Corpus Linguistics: Investigating the Trajectories of Public Health Messaging Online
Report
McClaughlin, E., Nichele, E., Adolphs, S., Barnard, P., Clos, J., Knight, D., …Lang, A. (2022). Privacy Preserving Corpus Linguistics: Investigating the Trajectories of Public Health Messaging Online. University of Nottingham: AHRC/UKRI

The Coronavirus Discourses project supports public health partners Public Health Wales, Public Health England, and NHS Education for Scotland in addressing key challenges that the coronavirus pandemic presents in terms of understanding the flow and i... Read More about Privacy Preserving Corpus Linguistics: Investigating the Trajectories of Public Health Messaging Online.