All Outputs (6)

FUTURE MACHINE: Making Myths & Designing Technology for a Responsible Future: Making Myths and Entanglement: Community engagement at the edge of participatory design and user experience (2023)
Conference Proceeding
Jacobs, R., Spence, J., Abbott, F., Chamberlain, A., Heim, W., Yemaoua Dayo, A., …King, J. (2023). FUTURE MACHINE: Making Myths & Designing Technology for a Responsible Future: Making Myths and Entanglement: Community engagement at the edge of participatory design and user experience. . https://doi.org/10.1145/3616961.3616979

This paper explores the unique methods and strategies employed by a team of artists, in collaboration with engineers, programmers, a climate scientist, researchers and members of the public, who have come together to create the Future Machine, with t... Read More about FUTURE MACHINE: Making Myths & Designing Technology for a Responsible Future: Making Myths and Entanglement: Community engagement at the edge of participatory design and user experience.

A genome-scale metabolic model of Cupriavidus necator H16 integrated with TraDIS and transcriptomic data reveals metabolic insights for biotechnological applications (2022)
Journal Article
Pearcy, N., Garavaglia, M., Millat, T., Gilbert, J. P., Song, Y., Hartman, H., …Minton, N. P. (2022). A genome-scale metabolic model of Cupriavidus necator H16 integrated with TraDIS and transcriptomic data reveals metabolic insights for biotechnological applications. PLoS Computational Biology, 18(5), Article e1010106. https://doi.org/10.1371/journal.pcbi.1010106

Exploiting biological processes to recycle renewable carbon into high value platform chemicals provides a sustainable and greener alternative to current reliance on petrochemicals. In this regard Cupriavidus necator H16 represents a particularly prom... Read More about A genome-scale metabolic model of Cupriavidus necator H16 integrated with TraDIS and transcriptomic data reveals metabolic insights for biotechnological applications.

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.

Gsmodutils: A python based framework for test-driven genome scale metabolic model development (2018)
Other
Gilbert, J. P., Pearcy, N., Norman, R., Millat, T., Winzer, K., King, J., …Twycross, J. (2018). Gsmodutils: A python based framework for test-driven genome scale metabolic model development

Motivation Genome scale metabolic models (GSMMs) are increasingly important for systems biology and metabolic engineering research as they are capable of simulating complex steady-state behaviour. Constraints based models of this form can include tho... Read More about Gsmodutils: A python based framework for test-driven genome scale metabolic model development.

Root hydrotropism is controlled via a cortex-specific growth mechanism (2017)
Journal Article
Dietrich, D., Pang, L., Kobayashi, A., Fozard, J. A., Boudolf, V., Bhosale, R., …Bennett, M. J. (2017). Root hydrotropism is controlled via a cortex-specific growth mechanism. Nature Plants, 3(6), Article 17057. https://doi.org/10.1038/nplants.2017.57

Plants can acclimate by using tropisms to link the direction of growth to environmental conditions. Hydrotropism allows roots to forage for water, a process known to depend on abscisic acid (ABA) but whose molecular and cellular basis remains unclear... Read More about Root hydrotropism is controlled via a cortex-specific growth mechanism.

Stochastic and deterministic multiscale models for systems biology: An auxin-transport case study (2010)
Journal Article
Twycross, J., Band, L. R., Bennett, M. J., King, J. R., & Krasnogor, N. (2010). Stochastic and deterministic multiscale models for systems biology: An auxin-transport case study. BMC Systems Biology, 4, https://doi.org/10.1186/1752-0509-4-34

Background: Stochastic and asymptotic methods are powerful tools in developing multiscale systems biology models; however, little has been done in this context to compare the efficacy of these methods. The majority of current systems biology modellin... Read More about Stochastic and deterministic multiscale models for systems biology: An auxin-transport case study.