Our team made both a deterministic and a stochastic model. There is a strong emphasis on exploring the dynamics given by the system's structure and the individual component's parameters in either type of model. The parameters were obtained from articles and databases such as Harvard Medical School's [http://bionumbers.hms.harvard.edu BioNumbers]. Another important source of information was the general binding rates included in the Kappa Simulator manual.


General assumptions:

●This model's scope is single cell. While the regulation steps were modeled through Hill equations, other reactions were treated under Michaelis-Menten assumptions, notably isomerizations and transport processes (i.e. those that involved energy consumption).

●The maximal transcription rate for the system species was obtained by dividing the maximum number of nucleotides processed by the RNA polymerase (i.e. maximum polymerase activity), by the length of the nucleotide sequence.

●Translational rates were obtained by getting the maximum number of amino acids added by the ribosome divided by the length of the protein in amino acids.

●The protein degradation rate is considered equal for all the protein species in the model.

●The degradation rate for mRNAs is equal for all the different species of mRNAs.

●The different binding sites of the same transcription factor have the same affinity to the TF.

●For each mRNA species, its concentration will be the sum of the production as affected by its respective promoter and the transcription factors that regulate it, minus the degradation of the mRNA at that time.

●For each protein, the change in its concentration depends in the amount of protein produced by translation minus the degradation rate of the protein.

●The Hill coefficients tend to be 2.

●The parameters of concentration were expressed in terms of molecules per cell (volume of a B.subtilis cell ~10^-14) and the time units were converted sec.

Parameters

NOTE: mol refers to molecules, not the unit mol

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