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All Outputs (6)

Metabolic modeling-based drug repurposing in Glioblastoma (2022)
Journal Article
Tomi-Andrino, C., Pandele, A., Winzer, K., King, J., Rahman, R., & Kim, D. (2022). Metabolic modeling-based drug repurposing in Glioblastoma. Scientific Reports, 12, Article 11189. https://doi.org/10.1038/s41598-022-14721-w

The manifestation of intra- and inter-tumor heterogeneity hinders the development of ubiquitous cancer treatments, thus requiring a tailored therapy for each cancer type. Specifically, the reprogramming of cellular metabolism has been identified as a... Read More about Metabolic modeling-based drug repurposing in Glioblastoma.

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.

Physicochemical and metabolic constraints for thermodynamics-based stoichiometric modelling under mesophilic growth conditions (2021)
Journal Article
Tomi-Andrino, C., Norman, R., Millat, T., Soucaille, P., Winzer, K., Barrett, D. A., …Kim, D. (2021). Physicochemical and metabolic constraints for thermodynamics-based stoichiometric modelling under mesophilic growth conditions. PLoS Computational Biology, 17(1), Article e1007694. https://doi.org/10.1371/journal.pcbi.1007694

© 2021 Tomi-Andrino et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source a... Read More about Physicochemical and metabolic constraints for thermodynamics-based stoichiometric modelling under mesophilic growth conditions.

Assessing the impact of physicochemical parameters in the predictive capabilities of thermodynamics-based stoichiometric approaches under mesophilic and thermophilic conditions (2020)
Working Paper
Tomi-Andrino, C., Norman, R., Millat, T., Soucaille, P., Winzer, K., Barrett, D. A., …Kim, D. Assessing the impact of physicochemical parameters in the predictive capabilities of thermodynamics-based stoichiometric approaches under mesophilic and thermophilic conditions

Metabolic engineering in the post-genomic era is characterised by the development of new methods for metabolomics and fluxomics, supported by the integration of genetic engineering tools and mathematical modelling. Particularly, constraint-based stoi... Read More about Assessing the impact of physicochemical parameters in the predictive capabilities of thermodynamics-based stoichiometric approaches under mesophilic and thermophilic conditions.

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.