Parameter scan for the model with addition of oxygen inhibition of LDH Version 1
Contains the estimated oxygen concentration and metabolite concentrations as wel as the model with addition of an oxygen inhibition parameter. Results: Addition of the oxygen inhibition term does not improve the modell with the current parameter set
SEEK ID: https://fairdomhub.org/data_files/2329?version=1
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2B_Oxygen_inhibition_of_Lactate_Dehydrogenase.zip
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Size: 115 KB
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Created: 7th Jan 2019 at 15:36
Last updated: 14th Jan 2019 at 16:00
Last used: 23rd Jul 2021 at 02:29
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Version 1 Created 7th Jan 2019 at 15:36 by Niels Zondervan
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https://orcid.org/0000-0001-7049-5334I am a researcher (PhD student) working at Wageningen University & Research as bioinformatician and modeller. I am working as part of the MycoSynVac (http://www.mycosynvac.eu/) project on dynamic modelling of central carbon metabolism in M. pneumoniae, to be extended to full dynamic modelling of metabolism to be implemented in a whole cell model. I am also looking into possibilities to improve standards in model generation using semantic technologies, improving automatic generation, annotation ...
Projects that do not fall under current programmes.
Projects: Manchester Institute for Biotechnology, ICYSB 2015 - International Practical Course in Systems Biology, iRhythmics, INBioPharm, EmPowerPutida, Systo models, MycoSynVac - Engineering Mycoplasma pneumoniae as a broad-spectrum animal vaccine, Multiscale modelling of state transitions in the host-microbiome-brain network, Extremophiles metabolsim, NAD COMPARTMENTATION, Agro-ecological modelling, Bergen(Ziegler lab) project AF-NADase, NAMPT affinity, Stress granules, Modelling COVID-19 epidemics, Bio-crop, ORHIZON-FAIR
Web page: Not specified
The MycoSynVac project AIMS at using cutting-edge synthetic biology methodologies to engineer Mycoplasma pneumoniae as a universal chassis for vaccination. Designing a universal Mycoplasma chassis that can be deployed as single- or multi-vaccine in a range of animal hosts. Annually, infections caused by Mycoplasma species in poultry, cows, and pigs result in multimillion Euro losses in the USA and Europe. There is no effective vaccination against many Mycoplasmas that infect pets, humans and farm ...
Programme: Independent Projects
Public web page: http://www.mycosynvac.eu/
- To develop a whole-cell dynamic model framework of the metabolism of M. pneumoniae
- To build upon M. pneumoniae models to develop a genome-scale, constraint-based model of M. hyopneumoniae for vaccine optimization
- To deploy the metabolic model(s) to: 1) the rational design and optimization of the vaccine chassis; 2) aid the development of a higher-growth rate chassis; 3) assist the development of a nutrient optimized a serum-free growth medium and; 4) assess, at genome scale, the metabolic ...
Submitter: Niels Zondervan
Studies: Core Model predictions, Core Model training, Core model predicting combined mutations and perturbations, Genome-scale, constraint-based metabolic modeling of M. hyopneumonia, Metabolomics measurements, Proteomics analysis, Transcriptomics of M. pneumoniae at different times of growth
Assays: 40 samples data analysis - metabolite correlation, 40 samples, OE mutants of glycolysis and pyruvate metabolism enzymes com..., All samples data, Comparison of Kcat values from the model and values from literature, Construction and training of the core model, Construction of a Genome Scale Metabolitic model of M. hyopneumoniae, Dynamic model simmulation pipeline, Metabolic control analysis (local and global), Metabolomics external metabolites measurements, Metabolomics internal metabolites, time series measurements, Proteomics assay, Transcriptomics assay of M. pneumoniae at diferent times of growth, Validation by simulating independent mutant and perturbation samples
Training of the core model, parameter estimation using Evolutionary Programming using metabolomics, proteomics and some flux data. The core model contains reactions in glycolysis, pyruvate metabolism and ATPase
Training of the model, parameter estimation using Evolutionary Programming using metabolomics, proteomics and some flux data.
Submitter: Niels Zondervan
Biological problem addressed: Model Analysis Type
Investigation: Modelling of M. pneumoniae metabolism
Study: Core Model training
