James Peter Gilbert
Gsmodutils: A python based framework for test-driven genome scale metabolic model development
Gilbert, James Peter; Pearcy, Nicole; Norman, Rupert; Millat, Thomas; Winzer, Klaus; King, John; Hodgman, Charlie; Minton, Nigel; Twycross, Jamie
Authors
Nicole Pearcy
Rupert Norman
Thomas Millat
Dr Klaus Winzer klaus.winzer@nottingham.ac.uk
ASSOCIATE PROFESSOR
Professor JOHN KING JOHN.KING@NOTTINGHAM.AC.UK
PROFESSOR OF THEORETICAL MECHANICS
Charlie Hodgman
Professor NIGEL MINTON NIGEL.MINTON@NOTTINGHAM.AC.UK
PROFESSOR OF APPLIED MOLECULAR MICROBIOLOGY
Dr JAMIE TWYCROSS JAMIE.TWYCROSS@NOTTINGHAM.AC.UK
ASSOCIATE PROFESSOR
Abstract
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 thousands of reactions and metabolites, with many crucial pathways that only become activated in specific simulation settings. However, despite their widespread use, power and the availability of tools to aid with the construction and analysis of large scale models, little methodology is suggested for the continued management of curated large scale models. For example, when genome annotations are updated or new understanding regarding behaviour of is discovered, models often need to be altered to reflect this. This is quickly becoming an issue for industrial systems and synthetic biotechnology applications, which require good quality reusable models integral to the design, build and test cycle.
Results As part of an ongoing effort to improve genome scale metabolic analysis, we have developed a test-driven development methodology for the continuous integration of validation data from different sources. Contributing to the open source technology based around COBRApy, we have developed the gsmodutils modelling framework placing an emphasis on test-driven design of models through defined test cases. Crucially, different conditions are configurable allowing users to examine how different designs or curation impact a wide range of system behaviours, minimising error between model versions.
Availability The software framework described within this paper is open source and freely available from http://github.com/SBRCNottingham/gsmodutils
Citation
Gilbert, J. P., Pearcy, N., Norman, R., Millat, T., Winzer, K., King, J., Hodgman, C., Minton, N., & Twycross, J. (2018). Gsmodutils: A python based framework for test-driven genome scale metabolic model development
Other Type | Other |
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Online Publication Date | Sep 29, 2018 |
Publication Date | Sep 29, 2018 |
Deposit Date | Apr 30, 2019 |
DOI | https://doi.org/10.1101/430116 |
Public URL | https://nottingham-repository.worktribe.com/output/1879890 |
Related Public URLs | https://www.biorxiv.org/content/10.1101/430116v1.full |
Additional Information | bioRxiv preprint |
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