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.

Explore some of the Open Access research from Mathematics & Statistics. Or explore all of Strathclyde's Open Access research...

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Jump to: 2020 | 2018 | 2016 | 2008 | 2007 | 2006 | 2005
Number of items: 9.

2020

Subramanian, Vigneshwari and Ratkova, Ekaterina and Palmer, David S. and Engkvist, Ola and Fedorov, Maxim V. and Llinas, Antonio (2020) Multi-solvent models for solvation free energy predictions using 3D-RISM hydration thermodynamic descriptors. Journal of Chemical Information and Modeling, 60 (6). pp. 2977-2988. ISSN 1549-9596

Fusani, Lucia and Palmer, David S. and Somers, Donald O. and Wall, Ian D. (2020) Exploring ligand stability in protein crystal structures using binding pose metadynamics. Journal of Chemical Information and Modeling, 60 (3). pp. 1528-1539. ISSN 1549-9596

Barrera, Maria Cecilia and Jorge, Miguel (2020) A polarization-consistent model for alcohols to predict solvation free energies. Journal of Chemical Information and Modeling, 60 (3). pp. 1352-1367. ISSN 1549-9596

2018

Ansari, Samiul M. and Palmer, David S. (2018) Comparative molecular field analysis using molecular integral equation theory. Journal of Chemical Information and Modeling. ISSN 1549-9596

2016

McDonagh, James and Palmer, David S. and van Mourik, Tanja and Mitchell, John B.O. (2016) Are the sublimation thermodynamics of organic molecules predictable? Journal of Chemical Information and Modeling. ISSN 1549-9596

2008

Hughes, L. D. and Palmer, D. S. and Nigsch, F. and Mitchell, J. B. (2008) Why are some properties more difficult to predict than others? A study of QSPR models of solubility, melting point, and Log P. Journal of Chemical Information and Modeling, 48 (1). pp. 220-232.

2007

Palmer, D. S. and O'Boyle, N. M. and Glen, R. C. and Mitchell, J. B. (2007) Random forest models to predict aqueous solubility. Journal of Chemical Information and Modeling, 47 (1). pp. 150-158.

2006

Cannon, E. O. and Bender, A. and Palmer, D. S. and Mitchell, J. B. (2006) Chemoinformatics-based classification of prohibited substances employed for doping in sport. Journal of Chemical Information and Modeling, 46 (6). pp. 2369-2380.

2005

Anthony, N.G. and Huchet, G. and Johnston, B.F. and Parkinson, B.F. and Suckling, C.J. and Waigh, R.D. and Mackay, S.P. (2005) In Silico Footprinting of Ligands Binding to the Minor Groove of DNA. Journal of Chemical Information and Modeling, 45 (6). pp. 1896-1907. ISSN 1549-9596

This list was generated on Tue Jul 7 23:46:35 2020 BST.