Picture of fish in sea

Open Access research that uses mathematical models to solve ecological problems...

Solving a variety of ecological and biological problems is the focus of marine population modelling research conducted within the Department of Mathematics & Statistics. Here research deploys mathematical models to better understanding issues relating to fish stock management, ecosystem dynamics, ocean currents, and the effects of multispecies interactions within diverse marine ecosystems.

Research work in marine population modelling interfaces with a number of other key research specialisms, including mathematical biology, epidemiology and statistical informatics, where investigations are improving human understanding of the behaviour of infectious diseases, particularly in relation to animal infections; but also the modelling of complex biological processes such as antibiotic prodcution in actinobacteria.

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Number of items: 3.

Vasantha, Gokula and Corney, Jonathan and Stuart, Struan and Sherlock, Andrew and Quigley, John and Purves, David (2020) A probabilistic design reuse index for engineering designs. Journal of Mechanical Design. ISSN 1050-0472

Stokes, Christopher and Masselink, Gerhard and Revie, Matthew and Scott, Timothy and Purves, David and Walters, Thomas (2017) Application of multiple linear regression and Bayesian belief network approaches to model life risk to beach users in the UK. Ocean and Coastal Management. ISSN 0964-5691 (In Press)

Miller, Ashley M. and Purves, David and McConnachie, Alex and Asquith, Darren L. and Batty, G. David and Burns, Harry and Cavanagh, Jonathan and Ford, Ian and McLean, Jennifer S. and Packard, Chris J. and Shiels, Paul G. and Turner, Helen and Velupillai, Yoga N. and Deans, Kevin A. and Welsh, Paul and McInnes, Iain B. and Sattar, Naveed (2012) Soluble ST2 associates with diabetes but not established cardiovascular risk factors : a new inflammatory pathway of relevance to diabetes? PLoS ONE, 7 (10). e47830. ISSN 1932-6203

This list was generated on Thu Jul 2 20:50:30 2020 BST.