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This model is a classic example of studying sol-gel transition in the context of ligand mediated (cell surface) receptor clustering.
It is recommended that you run Jupyter notebook - it has all the text below. This page is given just for convenience of those who don’t have an opportunity to run notebook
from NFsim_data_analyzer import *
from DataViz_NFsim import *
from MultiRun_BNG import *
# bngl file (BioNetGen model)
bng_file = './test_dataset/TLBR_model.bngl'
# Initialization of the Simulation Object
simObj = BNG_multiTrials(bng_file, t_end=400.0, steps=40, numRuns=20)
print(simObj)
simObj.runTrials(delSim=False)
print()
# analyze data across multiple trials
outpath = simObj.getOutPath()
molecules, numSite, counts, _ = simObj.getMolecules()
nfsObj = NFSim_output_analyzer(outpath)
nfsObj.process_gdatfiles()
nfsObj.process_speciesfiles(molecules, counts, numSite)
***** // *****
Class : BNG_multiTrials
File Path : ./test_dataset/TLBR_model.bngl
t_end : 400.0 seconds output_steps : 40
Number of runs: 20
Molecules: ['L', 'R']
Number of binding sites: [3, 2]
Species Counts: [300.0, 4200.0]
NFsim progress : [****************************************] 100%
Execution time : 21.5399 seconds
Processing gdat_files : [****************************************] 100%
Observables: {0: 'time', 1: 'CrossLinkedReceptors'}
Processing species_files : [****************************************] 100%
# Visualization
plotTimeCourse(outpath, obsList=[])
# 2A: Cluster size distribution (ACO: Average Cluster Occupancy)
plotClusterDist(outpath)
# You can plot a binned distribution by providing cluster size ranges
plotClusterDist(outpath, sizeRange=[1,10,500])
# 2B: Number of bonds per molecule
plotBondsPerMolecule(outpath)
# 2C: Bound fraction distribution
plotBoundFraction(outpath)
# 3A. Average composition of indivual clusters.
# Default is all the clusters present in the system. As before, adjust width and transparency (alpha) for visual clarity.
plotClusterComposition(outpath, specialClusters=[], width=0.25, alpha=0.5)
# You can look at the composition of a set of clusters (specialClusters) also
plotClusterComposition(outpath, specialClusters=[521, 531], width=0.15, alpha=0.7)
# 3B. Bondcount distribution of each molecular type
# You may provide a subset of molecules also
plotBondCounts(outpath, molecules=['L'])
plotBondCounts(outpath, molecules=['R'])