All Outputs (3)

Modelling Emerging Pollutants in Wastewater Treatment: A Case Study using the Pharmaceutical 17??ethinylestradiol (2019)
Journal Article
Acheampong, E., Dryden, I. L., Wattis, J. A., Twycross, J., Scrimshaw, M. D., & Gomes, R. L. (2019). Modelling Emerging Pollutants in Wastewater Treatment: A Case Study using the Pharmaceutical 17??ethinylestradiol. Computers and Chemical Engineering, 128, 477-487. https://doi.org/10.1016/j.compchemeng.2019.06.020

Mathematical modelling can play a key role in understanding as well as quantifying uncertainties surrounding the presence and fate of emerging pollutants in wastewater treatment processes (WWTPs). This paper presents for the first time a simplified e... Read More about Modelling Emerging Pollutants in Wastewater Treatment: A Case Study using the Pharmaceutical 17??ethinylestradiol.

Microarray Feature Selection and Dynamic Selection of Classifiers for Early Detection of Insect Bite Hypersensitivity in Horses (2019)
Conference Proceeding
Maciel Guerra, A., Figueredo, G. P., Von Zuben, F., Marti, E., Twycross, J., & Alcocer, M. J. (2019). Microarray Feature Selection and Dynamic Selection of Classifiers for Early Detection of Insect Bite Hypersensitivity in Horses. In 2019 IEEE Congress on Evolutionary Computation (CEC) (1157-1164). https://doi.org/10.1109/CEC.2019.8790319

Microarrays can be employed to better characterise allergies, as interactions between antibodies and allergens in mammals can be monitored. Once the joint dynamics of these elements in both healthy and diseased animals are understood, a model to pred... Read More about Microarray Feature Selection and Dynamic Selection of Classifiers for Early Detection of Insect Bite Hypersensitivity in Horses.

Gsmodutils: a python based framework for test-driven genome scale metabolic model development (2019)
Journal Article
Gilbert, J., Pearcy, N., Norman, R., Millat, T., Winzer, K., King, J., …Twycross, J. (2019). Gsmodutils: a python based framework for test-driven genome scale metabolic model development. Bioinformatics, 35(18), 3397-3403. https://doi.org/10.1093/bioinformatics/btz088

© 2019 The Author(s) 2019. Published by Oxford University Press. Motivation: Genome scale metabolic models (GSMMs) are increasingly important for systems biology and metabolic engineering research as they are capable of simulating complex steady-stat... Read More about Gsmodutils: a python based framework for test-driven genome scale metabolic model development.