PlaSMo model repository

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

Collection of models submitted to PLaSMo by Uriel Urquiza Garcia and automatically transferred to FAIRDOM Hub.

Collection of models submitted to PLaSMo by Tomasz Zielinski and automatically transferred to FAIRDOM Hub.

Collection of models submitted to PLaSMo by Alexandra Graf and automatically transferred to FAIRDOM Hub.

Collection of models submitted to PLaSMo by Carl Troein and automatically transferred to FAIRDOM Hub.

Collection of models submitted to PLaSMo by Richard Adams and automatically transferred to FAIRDOM Hub.

Collection of models submitted to PLaSMo by Jonathan Massheder and automatically transferred to FAIRDOM Hub.

Collection of models submitted to PLaSMo by Rob Smith and automatically transferred to FAIRDOM Hub.

Collection of models submitted to PLaSMo by Yin Hoon and automatically transferred to FAIRDOM Hub.

Collection of models submitted to PLaSMo by Martin Beaton and automatically transferred to FAIRDOM Hub.

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.

<strong>Original model</strong>: Arabidopsis clock model P2011.1.1 from
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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.<br><br><strong>Related Publications</strong></strong><br>Wilczek
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Detailed model of starch metabolism from Sorokina et al. BMC Sys Bio 2011. First upload is a draft.<br><br><strong>Related Publications</strong></strong><br>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<br><br><strong>Originally submitted to PLaSMo on 2011-08-12 15:34:00</strong></strong>
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The model shows how the <em>CONSTANS</em> gene and protein in <em>Arabidopsis thaliana</em> 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 (<a
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Andrew's work-in-progress P2012 version. <strong>NB KNOWN PROBLEMS</strong> 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.<br><br><strong>Originally submitted to PLaSMo on 2013-02-26 17:23:01</strong></strong>

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.<br><br><strong>Originally submitted to PLaSMo on 2013-09-13
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This is a version derived from a model from the article: <strong>Experimental validation of a predicted feedback loop in the multi-oscillator clock of Arabidopsis thaliana. </strong> Locke JC, Kozma-Bognár L, Gould PD, Fehér B, Kevei E, Nagy F, Turner MS, Hall A, Millar AJ <em>Mol. Syst. Biol.</em>2006;Volume:2;Page:59 <a href="http://www.ncbi.nlm.nih.gov/pubmed/17102804">17102804</a>, &nbsp; The model describes a three loop circuit of the Arabidopsis
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This version is derived from a model from the article: <strong>Extension of a genetic network model by iterative experimentation and mathematical analysis. </strong>Locke JC, Southern MM, Kozma-Bognár L, Hibberd V, Brown PE, Turner MS, Millar AJ <em>Mol. Syst. Biol. </em>2005; 1: 2005.0013 <a href="http://www.ncbi.nlm.nih.gov/pubmed/16729048">16729048</a>, &nbsp;SBML model of the interlocked feedback loop network The model describes the circuit
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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.&nbsp; &nbsp; Molecular Systems Biology <b>9</b> Article number: 650&nbsp;&nbsp;doi:10.1038/msb.2013.7 Published online: 19 March 2013 Citation: Molecular Systems Biology 9:650 Network balance <i>via</i> CRY signalling controls the <i>Arabidopsis</i>
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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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Related Publications
Me and Helena (2014). some book.
Moore A, Zielinski T, Millar AJ (2014). Online period estimation and determination of rhythmicity in circadian data, using the BioDare data infrastructure.. Methods in molecular biology (Clifton, N.J.). Retrieved from: doi.org/10.1007/978-1-4939-0700-7_2
Stein JM (1975). The effect of adrenaline and of alpha- and beta-adrenergic blocking agents on ATP concentration and on incorporation of 32Pi into
...

Related Publications
Me and Helena (2014). some book.
Moore A, Zielinski T, Millar AJ (2014). Online period estimation and determination of rhythmicity in circadian data, using the BioDare data infrastructure.. Methods in molecular biology (Clifton, N.J.). Retrieved from: doi.org/10.1007/978-1-4939-0700-7_2
Stein JM (1975). The effect of adrenaline and of alpha- and beta-adrenergic blocking agents on ATP concentration and on incorporation of 32Pi into
...

Related Publications
Me and Helena (2014). some book.
Moore A, Zielinski T, Millar AJ (2014). Online period estimation and determination of rhythmicity in circadian data, using the BioDare data infrastructure.. Methods in molecular biology (Clifton, N.J.). Retrieved from: doi.org/10.1007/978-1-4939-0700-7_2
Stein JM (1975). The effect of adrenaline and of alpha- and beta-adrenergic blocking agents on ATP concentration and on incorporation of 32Pi into
...

Related Publications
Me and Helena (2014). some book.
Moore A, Zielinski T, Millar AJ (2014). Online period estimation and determination of rhythmicity in circadian data, using the BioDare data infrastructure.. Methods in molecular biology (Clifton, N.J.). Retrieved from: doi.org/10.1007/978-1-4939-0700-7_2
Stein JM (1975). The effect of adrenaline and of alpha- and beta-adrenergic blocking agents on ATP concentration and on incorporation of 32Pi into
...

Related Publications
Me and Helena (2014). some book.
Moore A, Zielinski T, Millar AJ (2014). Online period estimation and determination of rhythmicity in circadian data, using the BioDare data infrastructure.. Methods in molecular biology (Clifton, N.J.). Retrieved from: doi.org/10.1007/978-1-4939-0700-7_2
Stein JM (1975). The effect of adrenaline and of alpha- and beta-adrenergic blocking agents on ATP concentration and on incorporation of 32Pi into
...

Related Publications
Me and Helena (2014). some book.
Moore A, Zielinski T, Millar AJ (2014). Online period estimation and determination of rhythmicity in circadian data, using the BioDare data infrastructure.. Methods in molecular biology (Clifton, N.J.). Retrieved from: doi.org/10.1007/978-1-4939-0700-7_2
Stein JM (1975). The effect of adrenaline and of alpha- and beta-adrenergic blocking agents on ATP concentration and on incorporation of 32Pi into
...

Related Publications
Me and Helena (2014). some book.
Moore A, Zielinski T, Millar AJ (2014). Online period estimation and determination of rhythmicity in circadian data, using the BioDare data infrastructure.. Methods in molecular biology (Clifton, N.J.). Retrieved from: doi.org/10.1007/978-1-4939-0700-7_2
Stein JM (1975). The effect of adrenaline and of alpha- and beta-adrenergic blocking agents on ATP concentration and on incorporation of 32Pi into
...

Related Publications
Me and Helena (2014). some book.
Moore A, Zielinski T, Millar AJ (2014). Online period estimation and determination of rhythmicity in circadian data, using the BioDare data infrastructure.. Methods in molecular biology (Clifton, N.J.). Retrieved from: doi.org/10.1007/978-1-4939-0700-7_2
Stein JM (1975). The effect of adrenaline and of alpha- and beta-adrenergic blocking agents on ATP concentration and on incorporation of 32Pi into
...

Related Publications
Me and Helena (2014). some book.
Moore A, Zielinski T, Millar AJ (2014). Online period estimation and determination of rhythmicity in circadian data, using the BioDare data infrastructure.. Methods in molecular biology (Clifton, N.J.). Retrieved from: doi.org/10.1007/978-1-4939-0700-7_2
Stein JM (1975). The effect of adrenaline and of alpha- and beta-adrenergic blocking agents on ATP concentration and on incorporation of 32Pi into
...

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

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  Published version is Biomodels ID 00412, http://www.ebi.ac.uk/compneur-srv/biomodels-main/BIOMD0000000412
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Data file for PLaSMo accesssion ID PLM_9, version 1

Data file for PLaSMo accesssion ID PLM_9, version 1

Data file for PLaSMo accesssion ID PLM_8, version 1

Data file for PLaSMo accesssion ID PLM_30, version 1

Data file for PLaSMo accesssion ID PLM_30, version 1

Data file for PLaSMo accesssion ID PLM_30, version 1

Data file for PLaSMo accesssion ID PLM_30, version 1

Data file for PLaSMo accesssion ID PLM_70, version 2

Data file for PLaSMo accesssion ID PLM_70, version 1

Data file for PLaSMo accesssion ID PLM_70, version 1

Originally submitted model file for PLaSMo accession ID PLM_71, version 2

Simplified model file for PLaSMo accession ID PLM_9, version 2 (use simplified if your software cannot read the file, e.g. Sloppy Cell)

Originally submitted model file for PLaSMo accession ID PLM_9, version 2

Simplified model file for PLaSMo accession ID PLM_9, version 1 (use simplified if your software cannot read the file, e.g. Sloppy Cell)

Originally submitted model file for PLaSMo accession ID PLM_9, version 1

Simplified model file for PLaSMo accession ID PLM_10, version 1 (use simplified if your software cannot read the file, e.g. Sloppy Cell)

Originally submitted model file for PLaSMo accession ID PLM_10, version 1

Simplified model file for PLaSMo accession ID PLM_8, version 1 (use simplified if your software cannot read the file, e.g. Sloppy Cell)

Originally submitted model file for PLaSMo accession ID PLM_8, version 1

Simplified model file for PLaSMo accession ID PLM_50, version 2 (use simplified if your software cannot read the file, e.g. Sloppy Cell)

What is PlaSMo?

PlaSMo stands for Plant Systems-biology Modelling; Ensuring the achievements of yesterday's Mathematical Modellers will be available for the Systems Biologists of tomorrow.

The original PlaSMo project description is included within the attached document.

Our aims

• To identify plant mathematical models useful to the UK plant systems biology community, which are currently in a variety of legacy formats and in danger of being
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