U2020.4 antimony version
This file was derived from U2020.3 by introducing the scalig factors in the required locations in the model. This files is used then for numerically rescaling the model for matching synthetic protein data.
SEEK ID: https://fairdomhub.org/models/830?version=1
1 item is associated with this Model:-
U2020.4.txt (Plain text document - 8.6 KB)
Organism: Arabidopsis thaliana
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Execution or visualisation environment: Not specified
Model image: No image specified
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Created: 15th Jan 2023 at 11:10
Last updated: 19th Dec 2024 at 11:28
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Version 2 (latest) Created 15th Jan 2023 at 11:12 by Uriel Urquiza Garcia
This is version is the result of the numerical rescaling using protein synthetic data. It has the scaling factors in the model file. The users does not need to add the scaling factors in this case
Version 1 (earliest) Created 15th Jan 2023 at 11:10 by Uriel Urquiza Garcia
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Related items
Projects: Millar group, PlaSMo model repository, PHYTOCAL: Phytochrome Control of Resource Allocation and Growth in Arabidopsis and in Brassicaceae crops, Light and plant development, Light control of leaf development, Toggle switch, Reduce Complexity (RCO) reconstruction, Model Driven Prime Editing, PULSE 2.0, Plant optogenetics
Institutions: University of Edinburgh, Heinrich Heine University of Düsseldorf
https://orcid.org/0000-0002-7975-5013
SynthSys is the University of Edinburgh's research organisation in interdisciplinary, Synthetic and Systems Biology, founded in 2012 as the successor to the Centre for Systems Biology at Edinburgh (CSBE).
Projects: Millar group, PHYTOCAL: Phytochrome Control of Resource Allocation and Growth in Arabidopsis and in Brassicaceae crops, TiMet, POP - the Parameter Optimisation Problem, Regulation of flowering time in natural conditions, PlaSMo model repository
Web page: http://www.synthsys.ed.ac.uk
Andrew Millar's research group, University of Edinburgh
Programme: SynthSys
Public web page: http://www.amillar.org
The dataset presents mathematical models of the gene regulatory network of the circadian clock, in the plant Arabidopsis thaliana. The work will be published as Urquiza-Garcia, Molina, Halliday and Millar, title "Abundant clock proteins point to missing molecular regulation in the plant circadian clock", in Molecular Systems Biology, 2025.
Starting from the U2019.3 and U2020.3 models, this project rescales parameters to match protein levels that were predicted using a simple model from the TiMet ...
Submitter: Andrew Millar
Studies: Construction of NanoLUC-tagged plants, Estimating DNA-binding affinities for Arabidopsis proteins, Measuring absolute levels of clock proteins with calibrated NanoLUC assays, Predicting absolute levels of clock proteins with a simple model, Recalibrating the clock models for absolute protein levels, to create mo..., Reproducibility documentation
Assays: Clock protein number determination with NanoLUC calibration, Clock proteins NanoLUC fusion raw data, Gatway maps of genomic regions of clock genes, In vivo bioluminescence of clock protein-NanoLUC fusions: example experi..., Jupyter notebook Predicting Protein Numbers, Propagating scaling factors into model parameters for U2019.4->U2019.5 a..., Protein level time series, Python packages, Reproducibility tool set, Selection of complemented transgenic lines, TiMet RNA timeseries data, promoter binding affinity calculations on the genome based on PBMs and E...
Submitter: Andrew Millar
Investigation: Absolute units for proteins in Arabidopsis cloc...
Assays: Jupyter notebook Predicting Protein Numbers, Protein level time series, TiMet RNA timeseries data
Jupyter lab notebook that contains the models and data that for predicting protein levels based on mRNA data from TiMet projecto
Submitter: Uriel Urquiza Garcia
Biological problem addressed: Model Analysis Type
Investigation: Absolute units for proteins in Arabidopsis cloc...
