Investigations
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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...
The dataset presents mathematical models of the gene regulatory network of the circadian clock, in the plant Arabidopsis thaliana. The work is published in Urquiza-Garcia and Millar, Testing the inferred transcription rates of a dynamic, gene network model in absolute units, In Silico Plants, 2021.
Starting from the P2011 model, this project corrects theoretical issues (EC steady state binding assumption) to form an intermediate model (first version U2017.1; published as U2019.1) model, rescales ...
