Models

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.

First version of enzyme-constrained model (ecModel) for Streptomyces albus J1074

First version of enzyme-constrained model (ecModel) for Pseudomonas putida KT2440

This is not my model

First draft of Genome-scale metabolic model (GEM) for reconstraction of flavonoids biosynthetic pathways. This model includes as a chassis , the Pseudomonas Putida GEM (iJN1411) .

For the spatio-temporal dynamics of bile transport, bile canalicular dilation, mechanical stimulation and transduction of YAP signaling during liver regeneration see the open access publication and its appendix:
Meyer et al. (2020) Bile canaliculi remodeling activates YAP via the actin cytoskeleton during liver regeneration. Molecular Systems Biology 16:e8985. https://doi.org/10.15252/msb.20198985

The model format is MorpheusML that can readily be loaded and run in the free and open source software
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Spatio-temporal liver zonation in mouse and human with Wnt-Hh crosstalk and transport are modeled using coupled partial differential equations. The model file is in MorpheusML format and can be opened in the free, open-source multicellular modeling software Morpheus (https://morpheus.gitlab.io). In Morpheus, the model will simulate the time course (movie) of dynamic liver zonation for a 2D cross-section of several liver lobules, showing the patterns of Wnt ligands, intracellular Wnt signaling,
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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.

The pathways focused on SARS-CoV infections curated in Reactome.
These pathways are work-in-progress.

This is an auto-generated model with COBRA Matlab toolbox. This model was deposited in BioModels [1] and assigned the identifier MODEL2010090003.

[1] Malik-Sheriff et al. BioModels — 15 years of sharing computational models in life science. Nucleic Acids Research. 2020 Jan, 48(D1):D407–415

This is an auto-generated model with COBRA Matlab toolbox. This model was deposited in BioModels [1] and assigned the identifier MODEL2010090002.

[1] Malik-Sheriff et al. BioModels — 15 years of sharing computational models in life science. Nucleic Acids Research. 2020 Jan, 48(D1):D407–415