Millar group

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 parameters to match absolute RNA levels from the TiMet WP1a RNA dataset of Flis et al. 2015 in U2019.2 (first version was U2017.2), then reoptimises globally to match RNA timeseries, period and amplitude constraints to produce the U2019.3 model. [The first version U2017.3 also matched the protein
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Project to test effects of temperature cycles on expression of Arabidopsis florigen gene FT, and whether these are mediated by temperature-dependent leaf development or temperature-specific FT expression, or both. Re-used and extended Arabidopsis Framework Model v1 to address this question. Led by Hannah Kinmonth-Schultz in Kim and Imaizumi labs, collaborating with Millar lab.

Data, FMv2 model and simulations for the Chew et al. 2017 paper (bioRxiv https://doi.org/10.1101/105437 ), mostly on the prr7 prr9 double mutant, with controls in lsf1 and prr7 single mutants.

Collection of models submitted to PLaSMo by Andrew Millar and automatically transferred to FAIRDOM Hub.

Project to test effects of natural compared to growth chamber 16:8 LD cycles, on expression of Arabidopsis flowering-time genes, and to define the genetic mechanisms and environmental triggers involved. Led by Young-Hun Song and Akane Kubota in the Imaizumi lab, with collaborators testing plants in parallel in Zurich and Edinburgh.

Click on Snapshot 2 to download data, models and analysis for Daniel Seaton et al.
biorXiv 2017 https://doi.org/10.1101/182071 and
Molecular Systems Biology, accepted Jan 2018, https://doi.org/10.15252/msb.20177962.
Note that the published paper cannot be fully linked into this record as the DOI above was not live when we made the Research Object from this Investigation on FAIRDOMHub.

Data, models and simulations for the Chew et al. 2014 paper (PNAS, https://doi.org/10.1073/pnas.1410238111), using wild-type Arabidopsis ecotype Col-0 in standard 12hL:12hD growth conditions, compared to La(er) or Fei-0 accessions, or to plants overexpressing a micro RNA (miR156).

The P2011 model was rescaled to match TiMet RNA data in clock mutants from Flis et al. 2015, attached here

Assays for model composition here, in order to share model files; potentially training and validation data in other Studies.

The models in this record were published in Flis et al. Royal Society Open Biology 2015. Their original IDs in the PlaSMo resource and IDs in Biomodels are given below. Please select files for download from the 'Related Items' list or the object tree/graph, below. 'SUBMITTED' is the original model version; 'SIMPLIFIED' removes SBML elements that were incompatible with SloppyCell software.

Original model: Arabidopsis clock model P2011.1.1 from Pokhilko et al. Mol Syst. Biol. 2012,
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Photothermal model for Arabidopsis development, as published, converted to Simile format by Yin-Hoon Chew. Note that the XML file is just a dummy SBML file, the .SML is the working model file. Simile can read csv files (as attached) for meteorological data (hourly temperature, sunrise, sunset). Users only need to change the directory of the input variables. I have also attached the set of parameter values for each genotype.Related PublicationsWilczek et al. (2009). Effects of Genetic Perturbation
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Detailed model of starch metabolism from Sorokina et al. BMC Sys Bio 2011. First upload is a draft.

Related Publications
Sorokina et al (2011). BMicroarray data can predict diurnal changes of starch content in the picoalga Ostreococcus.. BMC Systems Biology. Retrieved from: http://www.ncbi.nlm.nih.gov/pubmed/21352558

Originally submitted to PLaSMo on 2011-08-12 15:34:00

The model shows how the CONSTANS gene and protein in Arabidopsis thaliana forms a day-length sensor. It corresponds to Model 3 in the publication of Salazar et al. 2009. Matlab versions of all the models in the paper are attached to this record as a ZIP archive, as are all the data waveforms curated from the literature to constrain the model. Further information may be available via links from the authors web site (www.amillar.org). Simulation notes for SBML version of Model3 from Salazar et al.,
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Andrew's work-in-progress P2012 version. NB KNOWN PROBLEMS do not use lightly. Derived from PLM_49, after removing ABA regulation and tidying up the SBML in COPASI. Please see version comments for IMPORTANT notes.

Originally submitted to PLaSMo on 2013-02-26 17:23:01

Draft of MEP pathway for isoprenoid synthesis, created 2012-2013 by Oender Kartal in the Gruissem lab. He notes "It contains some annotations and references for the parameter values and rate equations and produces a stable steady state, so you can do some control analysis. It simulates day-metabolism, since the MEP Pathway is supposedly active during the day." Unpublished, for use by TiMet consortium only.

Originally submitted to PLaSMo on 2013-09-13 09:10:53

This is a version derived from a model from the article: Experimental validation of a predicted feedback loop in the multi-oscillator clock of Arabidopsis thaliana. Locke JC, Kozma-Bognár L, Gould PD, Fehér B, Kevei E, Nagy F, Turner MS, Hall A, Millar AJ Mol. Syst. Biol.2006;Volume:2;Page:59 17102804,   The model describes a three loop circuit of the Arabidopsis circadian clock. It provides initial conditions, parameter values and reactions for the production rates of the following species: LHY
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This version is derived from a model from the article: Extension of a genetic network model by iterative experimentation and mathematical analysis. Locke JC, Southern MM, Kozma-Bognár L, Hibberd V, Brown PE, Turner MS, Millar AJ Mol. Syst. Biol. 2005; 1: 2005.0013 16729048,  SBML model of the interlocked feedback loop network The model describes the circuit depicted in Fig. 4 and reproduces the simulations in Figure 5A and 5B. It provides initial conditions, parameter values and rules for the
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Temperature-sensitive version of Pokhilko 2010 Arabidopsis clock model, from Biomodels BIOMD00273, prepared by Mirela Domijan for the Gould et al. paper on cryptochrome influences on circadian rhythms.    Molecular Systems Biology 9 Article number: 650  doi:10.1038/msb.2013.7 Published online: 19 March 2013 Citation: Molecular Systems Biology 9:650 Network balance via CRY signalling controls the Arabidopsis circadian clock over ambient temperatures Gould, Ugarte, Domijan et al. doi:10.1038/msb.2013.7Originally
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A cell-level model of the Arabidopsis root elongation zone. This spatial model is divided up into biological cells which are further divided into simulation boxes. The original model was designed to investigate how canal cells can accumulate auxin over time rather than to investigate the transport of auxin through the canal cells per se. The main outputs of the simulations in the original paper were the steady state ratios of auxin in the canal cell protoplasts to that in the parenchyma cell
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A cell-level model of the Arabidopsis root elongation zone. This spatial model is divided up into biological cells which are further divided into simulation boxes. The original model was designed to investigate how canal cells can accumulate auxin over time rather than to investigate the transport of auxin through the canal cells per se. The main outputs of the simulations in the original paper were the steady state ratios of auxin in the canal cell protoplasts to that in the parenchyma cell
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Andrew's "ongoing work" record for the P2011 clock model. Many different versions, with annotations made during SBSI development in 2011-2013 - see version records.

Originally submitted to PLaSMo on 2012-05-31 22:18:27

P2011 model from PLM_43 version 6, optimised by Andrew Millar with SBSI PGA optimisation. A limited parameter set were free to optimise over < 10-fold range (less for RNA degradation rates), against ROBuST RNA data for clock genes in WT and mutants at 17C in LD, and period data in the same mutants in LL. The full SBSI costing is included, using costs from mid-June 2012 (note that costs returned with original optimisation in May were incorrectly reported).Originally submitted to PLaSMo on
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This model is termed P2012 and derives from the article: Modelling the widespread effects of TOC1 signalling on the plant circadian clock and its outputs. Alexandra Pokhilko, Paloma Mas & Andrew J Millar BMC Syst. Biol. 2013; 7: 23, submitted 10 Oct 2012 and published 19 March 2013. Link The model describes the circuit depicted in Fig. 1 of the paper (GIF will be attached soon). It updates the P2011 model from Pokhilko et al. Mol. Syst. Biol. 2012, Plasmo ID PLM_64, by including: TOC1 as a
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This model is termed P2011 and derives from the article: The clock gene circuit in Arabidopsis includes a repressilator with additional feedback loops. Alexandra Pokhilko, Aurora Piñas Fernández, Kieron D Edwards, Megan M Southern, Karen J Halliday & Andrew J Millar Mol. Syst. Biol. 2012; 8: 574, submitted 9 Aug 2011 and published 6 March 2012. Link Link to Supplementary Information, including equations. Minor errors in the published Supplementary Information are described in a file attached
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This model is one of five new parameter sets for P2011, published in Flis et al. Royal Society Open Biology 2015. They will be submitted to Biomodels when we have a PubMed ID for the paper. Derived from Original model: P2011.1.2 is public model ID PLM_71 version 1, http://www.plasmo.ed.ac.uk/plasmo/models/download.shtml?accession=PLM_71&version=1 This model P2011.6.1 is public model ID PLM_1044, with parameters optimised by Kevin Stratford using SBSInumerics software on the UK national
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This model is one of five new parameter sets for P2011, published in Flis et al. Royal Society Open Biology 2015. They will be submitted to Biomodels when we have a PubMed ID for the paper. Derived from Original model: P2011.1.2 is public model ID PLM_71 version 1, http://www.plasmo.ed.ac.uk/plasmo/models/download.shtml?accession=PLM_71&version=1 This model P2011.5.1 is public model ID PLM_1043, with parameters optimised by Kevin Stratford using SBSInumerics software on the UK national
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This section contains the links to the tools used for reproducing the computational results presented in U2019. This is required because SloppyCell is under the risk of becoming rotting code. Using Docker we can assure some persistence for the computational environment that allows to run SloppyCell.

The associated git repository can be found in https://github.com/jurquiza/Urquiza2019a.git which can be cloned.

The docker image can either be pulled from the docker hub site

docker pull
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Collection of clock models that rescale transcript variables to account for absolute units. The relationship between models is summarised in the attached 'model evolution' document and in more detail in the linked publications.
Each model is presented three times,
- without a light:dark cycle,
- with an ISSF (Adams et al. JBR 2012) that is set up for LD 12h:12h cycles, and
- with an ISSF that runs 10 LD cycles followed by an SBML Event that switches to constant light, matching published simulations.
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Model files for FMv1.5. The model is based on FMv1 of Chew et al. PNAS 2014, which is also in FAIRDOMHub and linked to the Model record as an 'Attribution'. FMv1 was extended in this work by Hannah Kinmonth-Schultz and Daniel Seaton, in Matlab.

Plant material
The same plant material used for transcriptome analysis in (Flis et al., 2016) was the basis of our proteome study. Briefly, Arabidopsis thaliana Col-0 plants were grown on GS 90 soil mixed in a ratio 2:1 (v/v) with vermiculite. Plants were grown for 1 week in a 16 h light (250 μmol m−2 s−1, 20 °C)/8 h dark (6 °C) regime followed by an 8 h light (160 μmol m−2 s−1, 20 °C)/16 h dark (16 °C) regime for one week. Plants were then replanted with five seedlings per pot, transferred for
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The models in this record were published in Flis et al. Royal Society Open Biology 2015. They will be submitted to Biomodels when we have a PubMed ID for the paper.

Original model: Arabidopsis clock model P2011.1.1 from Pokhilko et al. Mol Syst. Biol. 2012, http://dx.doi.org/10.1038/msb.2012.6

Published version is Biomodels ID 00412, http://www.ebi.ac.uk/compneur-srv/biomodels-main/BIOMD0000000412
Also public in Plasmo as PLM_64, with several versions, http://www.plasmo.ed.ac.uk/plasmo/models/model.shtml?accession=PLM_64
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The models in this record were published in Flis et al. Royal Society Open Biology 2015. They will be submitted to Biomodels when we have a PubMed ID for the paper.

Original model: Arabidopsis clock model P2011.1.1 from Pokhilko et al. Mol Syst. Biol. 2012, http://dx.doi.org/10.1038/msb.2012.6

Published version is Biomodels ID 00412, http://www.ebi.ac.uk/compneur-srv/biomodels-main/BIOMD0000000412
Also public in Plasmo as PLM_64, with several versions, http://www.plasmo.ed.ac.uk/plasmo/models/model.shtml?accession=PLM_64
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This model is one of five new parameter sets for P2011, published in Flis et al. Royal Society Open Biology 2015. They will be submitted to Biomodels when we have a PubMed ID for the paper. Derived from Original model: P2011.1.2 is public model ID PLM_71 version 1, http://www.plasmo.ed.ac.uk/plasmo/models/download.shtml?accession=PLM_71&version=1 This model P2011.6.1 is public model ID PLM_1044, with parameters optimised by Kevin Stratford using SBSInumerics software on the UK national
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This model is one of five new parameter sets for P2011, published in Flis et al. Royal Society Open Biology 2015. They will be submitted to Biomodels when we have a PubMed ID for the paper. Derived from Original model: P2011.1.2 is public model ID PLM_71 version 1, http://www.plasmo.ed.ac.uk/plasmo/models/download.shtml?accession=PLM_71&version=1 This model P2011.3.1 is public model ID PLM_1041, with parameters optimised by Kevin Stratford using SBSInumerics software on the UK national
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This model is termed P2011 and derives from the article: The clock gene circuit in Arabidopsis includes a repressilator with additional feedback loops. Alexandra Pokhilko, Aurora Piñas Fernández, Kieron D Edwards, Megan M Southern, Karen J Halliday & Andrew J Millar Mol. Syst. Biol. 2012; 8: 574, submitted 9 Aug 2011 and published 6 March 2012. Link Link to Supplementary Information, including equations. Minor errors in the published Supplementary Information are described in a file attached
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Photothermal model for Arabidopsis development, as published, converted to Simile format by Yin-Hoon Chew. Note that the XML file is just a dummy SBML file, the .SML is the working model file. Simile can read csv files (as attached) for meteorological data (hourly temperature, sunrise, sunset). Users only need to change the directory of the input variables. I have also attached the set of parameter values for each genotype.Related PublicationsWilczek et al. (2009). Effects of Genetic Perturbation
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Photothermal model for Arabidopsis development, as published, converted to Simile format by Yin-Hoon Chew. Note that the XML file is just a dummy SBML file, the .SML is the working model file. Simile can read csv files (as attached) for meteorological data (hourly temperature, sunrise, sunset). Users only need to change the directory of the input variables. I have also attached the set of parameter values for each genotype.Related PublicationsWilczek et al. (2009). Effects of Genetic Perturbation
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Detailed model of starch metabolism from Sorokina et al. BMC Sys Bio 2011. First upload is a draft.

Related Publications
Sorokina et al (2011). BMicroarray data can predict diurnal changes of starch content in the picoalga Ostreococcus.. BMC Systems Biology. Retrieved from: http://www.ncbi.nlm.nih.gov/pubmed/21352558

Originally submitted to PLaSMo on 2011-08-12 15:34:00

The model shows how the CONSTANS gene and protein in Arabidopsis thaliana forms a day-length sensor. It corresponds to Model 3 in the publication of Salazar et al. 2009. Matlab versions of all the models in the paper are attached to this record as a ZIP archive, as are all the data waveforms curated from the literature to constrain the model. Further information may be available via links from the authors web site (www.amillar.org). Simulation notes for SBML version of Model3 from Salazar et al.,
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The model shows how the CONSTANS gene and protein in Arabidopsis thaliana forms a day-length sensor. It corresponds to Model 3 in the publication of Salazar et al. 2009. Matlab versions of all the models in the paper are attached to this record as a ZIP archive, as are all the data waveforms curated from the literature to constrain the model. Further information may be available via links from the authors web site (www.amillar.org). Simulation notes for SBML version of Model3 from Salazar et al.,
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Andrew's work-in-progress P2012 version. NB KNOWN PROBLEMS do not use lightly. Derived from PLM_49, after removing ABA regulation and tidying up the SBML in COPASI. Please see version comments for IMPORTANT notes.Comments
No parameters constrained in version 1 file.
2013-02-26 17:31:26 3 amillar2 andrew.millar@ed.ac.uk
Compiled successfully in SBSI for optimisation.
2013-02-26 17:28:18 3 amillar2 andrew.millar@ed.ac.ukVersion Comments
Version 2 is file P2012_fin_NoABAv4.xml of 6th March.

It
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Andrew's work-in-progress P2012 version. NB KNOWN PROBLEMS do not use lightly. Derived from PLM_49, after removing ABA regulation and tidying up the SBML in COPASI. Please see version comments for IMPORTANT notes.Comments
No parameters constrained in version 1 file.
2013-02-26 17:31:26 3 amillar2 andrew.millar@ed.ac.uk
Compiled successfully in SBSI for optimisation.
2013-02-26 17:28:18 3 amillar2 andrew.millar@ed.ac.ukVersion Comments
Version 1 is file P2012_NoSinkNoABAParamsNom38_freshCopasi.xml
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Draft of MEP pathway for isoprenoid synthesis, created 2012-2013 by Oender Kartal in the Gruissem lab. He notes "It contains some annotations and references for the parameter values and rate equations and produces a stable steady state, so you can do some control analysis. It simulates day-metabolism, since the MEP Pathway is supposedly active during the day." Unpublished, for use by TiMet consortium only.

Originally submitted to PLaSMo on 2013-09-13 09:10:53

This is a version derived from a model from the article: Experimental validation of a predicted feedback loop in the multi-oscillator clock of Arabidopsis thaliana. Locke JC, Kozma-Bognár L, Gould PD, Fehér B, Kevei E, Nagy F, Turner MS, Hall A, Millar AJ Mol. Syst. Biol.2006;Volume:2;Page:59 17102804,   The model describes a three loop circuit of the Arabidopsis circadian clock. It provides initial conditions, parameter values and reactions for the production rates of the following species: LHY
...

This version is derived from a model from the article: Extension of a genetic network model by iterative experimentation and mathematical analysis. Locke JC, Southern MM, Kozma-Bognár L, Hibberd V, Brown PE, Turner MS, Millar AJ Mol. Syst. Biol. 2005; 1: 2005.0013 16729048,  SBML model of the interlocked feedback loop network The model describes the circuit depicted in Fig. 4 and reproduces the simulations in Figure 5A and 5B. It provides initial conditions, parameter values and rules for the
...

Temperature-sensitive version of Pokhilko 2010 Arabidopsis clock model, from Biomodels BIOMD00273, prepared by Mirela Domijan for the Gould et al. paper on cryptochrome influences on circadian rhythms.    Molecular Systems Biology 9 Article number: 650  doi:10.1038/msb.2013.7 Published online: 19 March 2013 Citation: Molecular Systems Biology 9:650 Network balance via CRY signalling controls the Arabidopsis circadian clock over ambient temperatures Gould, Ugarte, Domijan et al. doi:10.1038/msb.2013.7Version
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Mean values of clock gene RNA data in absolute units of RNA copies per cell (calculated from copies per gFW, / 25 million cells/gFW) from TiMet WP1.1, RNA dataset ros (from rosettes). Note the Col data are from WP1.1, not substituted with Col from the LD12:12 of the WP1.2 photoperiod data set, as they were in Flis et al. 2015. Note also that cL_m in these data is taken from CCA1 only, not the average of CCA1 and LHY as in the data sets used for optimisation of P2011.2.1 in Flis et al. 2015.

The
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Data for Figs. 2I, 2J, 2K in Chew et al. PNAS 2014
Fresh biomass, dry biomass (i.e. after baking out all water),
SLA - specific leaf area (area per g)

The same data are available on the BioDare resource, with additional experimental meta data on growth conditions.
BioDare ID 13790828881028, title "Physiology experiment using Col", the direct link is:
https://www.biodare.ed.ac.uk/robust/ShowExperiment.action?experimentId=13790828881028

Data for Figs. 3D, 3E in Chew et al. PNAS 2014
Fresh biomass, dry biomass (i.e. after baking out all water),
SLA - specific leaf area (area per g)
Also FMv1 model simulation results.

The same data are available on the BioDare resource, with additional experimental meta data on growth conditions.
BioDare ID 13790837647786, title "Physiology experiment using Fei", the direct link is:
https://www.biodare.ed.ac.uk/robust/ShowExperiment.action?experimentId=13790837647786

Data for Figs. 3A, 3B in Chew et al. PNAS 2014
Fresh biomass, dry biomass (i.e. after baking out all water),
SLA - specific leaf area (area per g)

Also contains model simulation data from the FMv1
The same data are available, with additional experimental meta data on growth conditions, from the BioDare resource:
BioDare experiment 13790834110003; title "Physiology experiment using Ler", the direct link is:
https://www.biodare.ed.ac.uk/robust/ShowExperiment.action?experimentId=13790834110003

Intact rosette is pictured, with plant number and genotype in handwritten labels, and ruler for scale.
Then dissected leaves are organised in sequence of age, if necessary with small cuts to let them lie flat.
Areas are then measured in image processing.

Data for Figs 3C, 3F and Supp 2 in Chew et al. PNAS 2014
Leaf number of the growing rosettes, from 4 to 37 days after sowing (DAS).
Data and also results of FMv1 model simulations.
Note that Fei-0 was previously tested by Mendez-Vigo et al, suggesting this line had a higher leaf appearance rate. We suggested that its larger final leaf number was more likely due to faster germination.

binary data file from "Hobo" environment multi-sensor + data logger, located next to the plants used in the experiment. Usually read in HOBOware software, free from Onsetcomp.com. Useful temperature record. Though light levels can usefully show changes they are not well calibrated.

Fig 5D

Figure 5D

Data for Fig. Supp 7B in Chew et al. PNAS 2014
Leaf number of the growing rosettes, from 5 to 37 days after sowing.
Data and also results of three FMv1 model simulations, with default, fitted and linear (i.e. no juvenile-adult transition in phyllochron)

Data for Figs. 5D, 5E and Supp 7C in Chew et al. PNAS 2014
FW - fresh weight
DW - dry weight (i.e. after baking out all water)
SLA - specific leaf area (area per g mass), indicates leaf thickness
Indiv, data for individual leaves rather than rosette

Experiment conducted in early April 2014
Intact rosette is pictured, with plant number and genotype in handwritten labels, and ruler for scale.
Then dissected leaves are organised in sequence of age,
if necessary with small cuts to let them lie flat.

Areas are then measured in image processing.

Supplementary information file from Chew et al. PNAS 2014, including full model description for Arabidopsis Framework Model v1, model simulations and experimental validations.

Microarray data at end of day (ED) and end of night (EN) in 4, 6, 8, 12, and 18h photoperiods.

Mean and standard deviation of protein abundances in 6h, 8h, 12h, and 18h photoperiods.

Results of the statistical analysis, identifying proteins that change in abundance significantly across photoperiods.

Proteomics data for N15 incorporation into protein in Ostreococcus grown in 12L:12D light:dark cycles.

Quantitative proteomic analysis of Cyanothece ATCC51142 grown in 12L:12D light:dark cycles, using partial metabolic labeling and LC-MS analysis.

U2019.3 that simulates light condition with ISSF

U2020.2 that simulates light condition with ISSF

U2019.1 that simulates light condition with ISSF

U2019.3 that simulates light condition with ISSF

U2019.2 that simulates light condition with ISSF

U2019.1 that simulates light condition with ISSF

Model derived from P2011.1.2 in which the steady state assumptions for the Evening complex in P2011 were eliminated. After eliminating these assumptions the model was fitted to the original dynamics of P2011.1.2 for the networks WT, lhycca1, prr79, toc1, gi, ztl. In particular for the lhycca1 double mutant only the repressive "arms" (edges) for cL were set to zero. The parameter values or cP and for COP1 variables were fixed as these have been fitted before in Pokhilko et al 2012 Mol Sys Bio.

U2020.5 derived model in which the was fitted to TiMet data mutants data set. Fixed parameters are scaling factors, COP1 and cP parameters.
The rest of the parameters were left optimisable. The networks used in the fitting include WT, lhycca1, prr79, toc1, gi and ztl.
The ztl network was only used for fixing the period in this mutant. Then final parameter values for transcription rated were obtained by taking the
product of scaling factor and either transcription or translation, the latter required
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Model derived from U2020.4 by fitting the scaling factors for matching TiMet data set and mutant networks.

Model derived from U2020.1 for which the way the PRRs are regulated is modified. Repression mechanism introduced Instead of activation between the PRRs for producing the wave of expression. This is inspired in the result of three models P2012, F2014 and F2016. P2012 introduced TOC1 repression in earlier genes relative to its expression. F2014 introduced also the backward repression of PRR9 |-- PRR7 |--- PRR5, TOC1. However little attention was given to why there is a sharper expression pattern.
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U2020.2 derived model in which the was fitted to TiMet data mutants data set. Fixed parameters are scaling factors, COP1 and cP parameters. The rest of the parameters were left optimisable. The networks used in the fitting include WT, lhycca1, prr79, toc1, gi and ztl. The ztl network was only used for fixing the period in this mutant. Then final parameter values for transcription rated were obtained by taking the product of scaling factor and either transcription or translation, the latter required
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Model derived from U2020.1 in which the transcription rates were rescaled to match the scale of TiMet data set. The gmX parameter in the model were fitted numerically. This has equivalent dynamics to P2011.1.2.

Framework Model for Arabidopsis vegetative growth, version 2 (FMv2), as described in Chew et al. bioRxiv 2017 (https://doi.org/10.1101/105437; please see linked Article file).

The FMv2 model record on FAIRDOMHub has the following versions, which represent the same FMv2 model:
Version 1 is an archive of the github repository of MATLAB code for the Framework Model v2, downloaded from https://github.com/danielseaton/frameworkmodel on 06/02/17. This version was not licensed for further use and was
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Arabidopsis clock model P2011.6.1 SBML imported into Copasi 4.8 and saved as native Copasi file.

Outline report of joint research conducted during MSBnet-funded visit of Sanu Shameer to Millar lab

This file contains the dependencies required for running SloppyCell and Tellurium together using Jupyter notebooks. It can be used to create a Docker image by executing the command

docker build user/image:version .

The image used for the project can be pulled from Docker hub by typing

docker pull uurquiza/urquiza2019a_tellurium_sloppycell:latest

Contains the summary of model evolution for the Arabidopsis clock in absolute units. In these process two alternative architectures were proposed and fitted to Flis A et al 2015 Open Biology.