Dr Vinny Davies

  • Lecturer (Statistics)

Biography

Dr Davies is a lecturer in Statistics in the School of Mathematics and Statistics specilising in computational biology and computational methods for statistics and machine learning. He completed his Ph.D. within the School of Mathematics and Statistics where he focused on variable selection models for selecting antigenic sites in virus evolution. He then completed several post-docteral research positions in both the schools of Statistics and Computing Science, as well as spending time as a Biostatistician at the University of Leeds. He recently returned to the School of Mathematics and Statistics where his research interests will focus on methods on the interface between Statistics and Machine Learning. He has a particular interest in Computational Metabolomics, but a general interest in applying statistical and machine learning methods to any biological, chemical or health problem.

If you are interested in a doing a Ph.D., please take a look at the Supervision section or email me directly.

Research interests

Publications

List by: Type | Date

Jump to: 2021 | 2020 | 2019 | 2017 | 2016 | 2014 | 2013
Number of items: 18.

2021

Scott, E. M. , Davies, V. , Nolan, A. M., Noble, C. E., Dowgray, N. J., German, A. J., Wiseman-Orr, M. L. and Reid, J. (2021) Validity and responsiveness of the generic health-related quality of life instrument (VetMetrica™) in cats with osteoarthritis. Comparison of vet and owner impressions of quality of life impact. Frontiers in Veterinary Science, 8, 733812. (doi: 10.3389/fvets.2021.733812)

Davies, V. , Wandy, J., Weidt, S., van der Hooft, J. J.J. , Miller, A. , Daly, R. and Rogers, S. (2021) Rapid development of improved data-dependent acquisition strategies. Analytical Chemistry, 93(14), pp. 5676-5683. (doi: 10.1021/acs.analchem.0c03895) (PMID:33784814) (PMCID:PMC8047769)

Davies, V. , Reid, J. and Scott, E. M. (2021) Optimisation of scores generated by an online feline health–related quality of life (HRQL) instrument to assist the veterinary user interpret its results. Frontiers in Veterinary Science, 7, 601304. (doi: 10.3389/fvets.2020.601304) (PMID:33490133) (PMCID:PMC7815521)

2020

Arnold, K. F., Davies, V. , de Kamps, M., Tennant, P. W.G., Mbotwa, J. and Gilthorpe, M. S. (2020) Reflection on modern methods: generalized linear models for prognosis and intervention—theory, practice and implications for machine learning. International Journal of Epidemiology, 49(6), pp. 2074-2082. (doi: 10.1093/ije/dyaa049) (PMID:32380551) (PMCID:PMC7825942)

Davies, V. , Scott, E. M. , Wright, A. K. and Reid, J. (2020) Development of an early warning system for owners using a validated health-related quality of life (HRQL) instrument for companion animals and its use in a large cohort of dogs. Frontiers in Veterinary Science, 7, 575795. (doi: 10.3389/fvets.2020.575795) (PMID:33195573) (PMCID:PMC7541963)

2019

Davies, V. , Noè, U. , Lazarus, A., Gao, H. , Macdonald, B. , Berry, C. , Luo, X. and Husmeier, D. (2019) Fast parameter inference in a biomechanical model of the left ventricle by using statistical emulation. Journal of the Royal Statistical Society: Series C (Applied Statistics), 68(5), pp. 1555-1576. (doi: 10.1111/rssc.12374) (PMID:31762497) (PMCID:PMC6856984)

Wandy, J., Davies, V. , van der Hooft, J. J.J. , Weidt, S., Daly, R. and Rogers, S. (2019) In silico optimization of mass spectrometry fragmentation strategies in metabolomics. Metabolites, 9(10), 219. (doi: 10.3390/metabo9100219) (PMID:31600991)

Davies, V. , Reid, J., Wiseman-Orr, M. L. and Scott, E. M. (2019) Optimising outputs from a validated online instrument to measure health-related quality of life (HRQL) in dogs. PLoS ONE, 14(9), e0221869. (doi: 10.1371/journal.pone.0221869) (PMID:31532799) (PMCID:PMC6750605)

Husmeier, D. , Lazarus, A., Noè, U. , Davies, V. , Borowska, A. , Macdonald, B. , Gao, H. , Berry, C. and Luo, X. (2019) Statistical Emulation of Cardiac Mechanics: an Important Step Towards a Clinical Decision Support System. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 29. ISBN 9781927877647 (doi: 10.11159/icsta19.29)

Davies, V. , Harvey, W. T., Reeve, R. and Husmeier, D. (2019) Improving the identification of antigenic sites in the H1N1 Influenza virus through accounting for the experimental structure in a sparse hierarchical Bayesian model. Journal of the Royal Statistical Society: Series C (Applied Statistics), 68(4), pp. 859-885. (doi: 10.1111/rssc.12338) (PMID:31598013) (PMCID:PMC6774336)

Noè, U. , Lazarus, A., Gao, H. , Davies, V. , Macdonald, B. , Mangion, K., Berry, C. , Luo, X. and Husmeier, D. (2019) Gaussian process emulation to accelerate parameter estimation in a mechanical model of the left ventricle: a critical step towards clinical end-user relevance. Journal of the Royal Society: Interface, 16(156), 20190114. (doi: 10.1098/rsif.2019.0114) (PMID:31266415) (PMCID:PMC6685034)

Moesta, A., Hours, M.A., Boutigny, L., Davies, V. , Kelly, S., Mougeotc, I. and Reid, J. (2019) A Weight Loss Diet With Alpha-casozepine and L-tryptophane Improves Health Related Quality of Life in Dogs. In: 12th International Veterinary Behaviour Meeting 2019, Washington, D.C., USA, 30 Jul - 01 Aug 2019, pp. 66-74. ISBN 9781527242326

2017

Davies, V. , Reeve, R. , Harvey, W. T., Maree, F. F. and Husmeier, D. (2017) A sparse hierarchical Bayesian model for detecting relevant antigenic sites in virus evolution. Computational Statistics, 32(3), pp. 803-843. (doi: 10.1007/s00180-017-0730-6)

2016

Davies, V. , Reeve, R. , Harvey, W. T. and Husmeier, D. (2016) Selecting random effect components in a sparse hierarchical Bayesian model for identifying antigenic variability. In: Computational Intelligence Methods for Bioinformatics and Biostatistics: 12th International Meeting, CIBB 2015, Naples, Italy, September 10-12, 2015, Revised Selected Papers. Series: Lecture Notes in Computer Science (9874). Springer, pp. 14-27. ISBN 9783319443317 (doi: 10.1007/978-3-319-44332-4_2)

2014

Davies, V. , Reeve, R. , Harvey, W., Maree, F. and Husmeier, D. (2014) Sparse Bayesian variable selection for the identification of antigenic variability in the Foot-and-Mouth disease virus. Proceedings of Machine Learning Research, 33, pp. 149-158.

Davies, V. and Husmeier, D. (2014) Modelling transcriptional regulation with Gaussian processes. In: Valente, A. X.C.N., Sarkar, A. and Gao, Y. (eds.) Recent Advances in Systems Biology Research. Nova Science Publishers: New York, pp. 157-184. ISBN 9781629487366

2013

Chanialidis, C. , Craigmile, P., Davies, V. , Dean, N. , Evers, L. , Filiippone, M., Gupta, M. , Ray, S. and Rogers, S. (2013) Discussion of Henning and Liao: How to find an appropriate clustering for mixed type variables with application to socio-economic stratification. Journal of the Royal Statistical Society: Series C. 62, 309-369. Discussion Paper. Springer. (doi: 10.1111/j.1467-9876.2012.01066.x).

Davies, V. and Husmeier, D. (2013) Assessing the impact of non-additive noise on modelling transcriptional regulation with Gaussian processes. In: Muggeo, V.M.R., Capursi, V., Boscaino, G. and Lovison, G. (eds.) Proceedings of the 28th International Workshop on Statistical Modelling. Gruppo Istituto Poligrafico Europeo SRL, pp. 559-562. ISBN 9788896251492

This list was generated on Fri Jan 21 14:27:57 2022 GMT.
Number of items: 18.

Articles

Scott, E. M. , Davies, V. , Nolan, A. M., Noble, C. E., Dowgray, N. J., German, A. J., Wiseman-Orr, M. L. and Reid, J. (2021) Validity and responsiveness of the generic health-related quality of life instrument (VetMetrica™) in cats with osteoarthritis. Comparison of vet and owner impressions of quality of life impact. Frontiers in Veterinary Science, 8, 733812. (doi: 10.3389/fvets.2021.733812)

Davies, V. , Wandy, J., Weidt, S., van der Hooft, J. J.J. , Miller, A. , Daly, R. and Rogers, S. (2021) Rapid development of improved data-dependent acquisition strategies. Analytical Chemistry, 93(14), pp. 5676-5683. (doi: 10.1021/acs.analchem.0c03895) (PMID:33784814) (PMCID:PMC8047769)

Davies, V. , Reid, J. and Scott, E. M. (2021) Optimisation of scores generated by an online feline health–related quality of life (HRQL) instrument to assist the veterinary user interpret its results. Frontiers in Veterinary Science, 7, 601304. (doi: 10.3389/fvets.2020.601304) (PMID:33490133) (PMCID:PMC7815521)

Arnold, K. F., Davies, V. , de Kamps, M., Tennant, P. W.G., Mbotwa, J. and Gilthorpe, M. S. (2020) Reflection on modern methods: generalized linear models for prognosis and intervention—theory, practice and implications for machine learning. International Journal of Epidemiology, 49(6), pp. 2074-2082. (doi: 10.1093/ije/dyaa049) (PMID:32380551) (PMCID:PMC7825942)

Davies, V. , Scott, E. M. , Wright, A. K. and Reid, J. (2020) Development of an early warning system for owners using a validated health-related quality of life (HRQL) instrument for companion animals and its use in a large cohort of dogs. Frontiers in Veterinary Science, 7, 575795. (doi: 10.3389/fvets.2020.575795) (PMID:33195573) (PMCID:PMC7541963)

Davies, V. , Noè, U. , Lazarus, A., Gao, H. , Macdonald, B. , Berry, C. , Luo, X. and Husmeier, D. (2019) Fast parameter inference in a biomechanical model of the left ventricle by using statistical emulation. Journal of the Royal Statistical Society: Series C (Applied Statistics), 68(5), pp. 1555-1576. (doi: 10.1111/rssc.12374) (PMID:31762497) (PMCID:PMC6856984)

Wandy, J., Davies, V. , van der Hooft, J. J.J. , Weidt, S., Daly, R. and Rogers, S. (2019) In silico optimization of mass spectrometry fragmentation strategies in metabolomics. Metabolites, 9(10), 219. (doi: 10.3390/metabo9100219) (PMID:31600991)

Davies, V. , Reid, J., Wiseman-Orr, M. L. and Scott, E. M. (2019) Optimising outputs from a validated online instrument to measure health-related quality of life (HRQL) in dogs. PLoS ONE, 14(9), e0221869. (doi: 10.1371/journal.pone.0221869) (PMID:31532799) (PMCID:PMC6750605)

Davies, V. , Harvey, W. T., Reeve, R. and Husmeier, D. (2019) Improving the identification of antigenic sites in the H1N1 Influenza virus through accounting for the experimental structure in a sparse hierarchical Bayesian model. Journal of the Royal Statistical Society: Series C (Applied Statistics), 68(4), pp. 859-885. (doi: 10.1111/rssc.12338) (PMID:31598013) (PMCID:PMC6774336)

Noè, U. , Lazarus, A., Gao, H. , Davies, V. , Macdonald, B. , Mangion, K., Berry, C. , Luo, X. and Husmeier, D. (2019) Gaussian process emulation to accelerate parameter estimation in a mechanical model of the left ventricle: a critical step towards clinical end-user relevance. Journal of the Royal Society: Interface, 16(156), 20190114. (doi: 10.1098/rsif.2019.0114) (PMID:31266415) (PMCID:PMC6685034)

Davies, V. , Reeve, R. , Harvey, W. T., Maree, F. F. and Husmeier, D. (2017) A sparse hierarchical Bayesian model for detecting relevant antigenic sites in virus evolution. Computational Statistics, 32(3), pp. 803-843. (doi: 10.1007/s00180-017-0730-6)

Davies, V. , Reeve, R. , Harvey, W., Maree, F. and Husmeier, D. (2014) Sparse Bayesian variable selection for the identification of antigenic variability in the Foot-and-Mouth disease virus. Proceedings of Machine Learning Research, 33, pp. 149-158.

Book Sections

Davies, V. , Reeve, R. , Harvey, W. T. and Husmeier, D. (2016) Selecting random effect components in a sparse hierarchical Bayesian model for identifying antigenic variability. In: Computational Intelligence Methods for Bioinformatics and Biostatistics: 12th International Meeting, CIBB 2015, Naples, Italy, September 10-12, 2015, Revised Selected Papers. Series: Lecture Notes in Computer Science (9874). Springer, pp. 14-27. ISBN 9783319443317 (doi: 10.1007/978-3-319-44332-4_2)

Davies, V. and Husmeier, D. (2014) Modelling transcriptional regulation with Gaussian processes. In: Valente, A. X.C.N., Sarkar, A. and Gao, Y. (eds.) Recent Advances in Systems Biology Research. Nova Science Publishers: New York, pp. 157-184. ISBN 9781629487366

Davies, V. and Husmeier, D. (2013) Assessing the impact of non-additive noise on modelling transcriptional regulation with Gaussian processes. In: Muggeo, V.M.R., Capursi, V., Boscaino, G. and Lovison, G. (eds.) Proceedings of the 28th International Workshop on Statistical Modelling. Gruppo Istituto Poligrafico Europeo SRL, pp. 559-562. ISBN 9788896251492

Research Reports or Papers

Chanialidis, C. , Craigmile, P., Davies, V. , Dean, N. , Evers, L. , Filiippone, M., Gupta, M. , Ray, S. and Rogers, S. (2013) Discussion of Henning and Liao: How to find an appropriate clustering for mixed type variables with application to socio-economic stratification. Journal of the Royal Statistical Society: Series C. 62, 309-369. Discussion Paper. Springer. (doi: 10.1111/j.1467-9876.2012.01066.x).

Conference Proceedings

Husmeier, D. , Lazarus, A., Noè, U. , Davies, V. , Borowska, A. , Macdonald, B. , Gao, H. , Berry, C. and Luo, X. (2019) Statistical Emulation of Cardiac Mechanics: an Important Step Towards a Clinical Decision Support System. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 29. ISBN 9781927877647 (doi: 10.11159/icsta19.29)

Moesta, A., Hours, M.A., Boutigny, L., Davies, V. , Kelly, S., Mougeotc, I. and Reid, J. (2019) A Weight Loss Diet With Alpha-casozepine and L-tryptophane Improves Health Related Quality of Life in Dogs. In: 12th International Veterinary Behaviour Meeting 2019, Washington, D.C., USA, 30 Jul - 01 Aug 2019, pp. 66-74. ISBN 9781527242326

This list was generated on Fri Jan 21 14:27:57 2022 GMT.

Supervision

I am looking for potential PhD students across a range of subjects and have a number of projects available below. Please contact me if you wish to discuss these or any other projects further.

Metabolomics DIA Resolver

In metabolomics we take a sample (blood, urine, etc) and put it through a mass spectrometer. The mass spectrometer scans the sample in multiple ways to help us work out what metabolites can be found in the sample. Identifying these metabolites can be useful for clinical trials, disease diagnosis and progression and various other medical applications. There are various way of choosing the scans, but in one particular method (DIA) we often see multiple fragments from multiple metabolites in a single scan. In order to identify the metabolites we need to work out which fragments belong to which metabolites. There are two possible projects that could come from this which can both be tested via a virtual mass spectrometer that we have recently created (ViMMS). The first is to design a new Bayesian model to use existing data to help us link the fragments to their metabolites, existing methods are currently quite basic. This project will involve more Bayesian modelling, but will also have to link with existing work in Python. The second option would be to design new ways of collecting the data that could provide more information from a sample, we have previously done some related work. This second option would involve more programming (Python) and less Bayesian statistics most likely, but the projects would certainly be closely related. In the case of each project, some initial work would need to be done analysing existing methods using our virtual mass spectrometer.

Bayesian Modelling of Antigenic Variability in Viruses

Viruses often mutate as we have seen with Covid-19 recently. When we create vaccines we usually use parts of a previous virus strain as part of the process. What this means (roughly) is that the vaccine will protect people against virus strains that are antigenically similar to the virus strain from which the vaccine was created. If new virus strains sufficiently mutate away from the virus strain of the vaccine, then the vaccine will become ineffective. The mutations occur in the amino acids in the proteins, but not all mutations are likely to cause problems. I have previously developed a Bayesian model to identify the relevant mutations. One of the options for this project would be to further develop this model by taking into account additional sources of information in the model. The other option would be to develop a new method which was able to predict which mutations we are likely to see in the future based on previous viruses and their current prosperity.

 

 

Teaching

This year I will be teaching on the online MSc Data Analytics, where I will be teaching on the following courses:

- Data programming in Python

- Large-Scale Computing for Data Analytics

I will also be supervising a number of dissertation projects.

Research datasets

Jump to: 2021 | 2019
Number of items: 2.

2021

Davies, V. , Wandy, J., Weidt, S., van der Hooft, J., Miller, A. , Daly, R. and Rogers, S. (2021) Rapid Development of Improved Data-Dependent Acquisition Strategies. [Data Collection]

2019

Wandy, J., Davies, V. , van der Hooft, J., Weidt, S., Daly, R. and Rogers, S. (2019) In-silico Optimisation of Mass Spectrometry Fragmentation Strategies in Metabolomics. [Data Collection]

This list was generated on Fri Jan 21 14:27:59 2022 GMT.