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circadian-amplitude-metrics's Introduction

These are the python source files used to generate the figures in the manuscript P. C. St. John, S. R. Taylor, J. H. Abel, and F. J. Doyle, “Amplitude Metrics for Cellular Circadian Bioluminescence Reporters,” Biophys. J., vol. 107, no. 11, pp. 2712–2722, Dec. 2014. These files are provided in their raw state without significant documentation in the hopes that they may prove useful for an interested reader.

PRE-REQUISITES

SOFTWARE VERSION WEBSITE
python 2.7.3 python.org
numpy 1.6.1 numpy.org
scipy 0.13.3 scipy.org
matplotlib 1.3.1 matplotlib.org
casadi 1.5.0 casadi.org
svg.path 1.1 https://pypi.python.org/pypi/svg.path

FILE DESCRIPTIONS

fig1.py                 : python code to generate figure 1
fig2.py                 : python code to generate figure 2
fig3.py                 : python code to generate figure 3
fig4.py                 : python code to generate figure 4
fig5_degmodel_arcs.dat  : pre-calculated differential ARCs for the model from
                          Hirota et al, 2012
fig5_fit.p              : pre-calculated exponential sinusoid fit to the data
                          of Ukai et al, 2007
fig5.py                 : python code to generate figure 5
figS1.py                : python code to generate figure S1
figS2.py                : python code to generate figure S2
figS2_stochastic_data.p : pre-calculated stochastic model trajectories for the
                          15^2 cells shown in supplemental movies

data/
__init__.py       : dummy file to allow package loading
MelanopsinData.py : File to process data from Ukai et al SVG
mel_n.txt         : svg path data for figure of control trajectory
mel_p.txt         : svg path data for figure of mel-positive trajectory

tools/
__init__.py        : n/a
Amplitude.py       : main file to calculate phase pdfs and single-cell ARCS
Bioluminescence.py : utility functions to detrend and fit sinusoidal data
Odesol.py          : class to calculate features of limit-cycle models
PlotOptions.py     : various matplotlib options to control output plots
Utilities.py       : Interpolation and plotting utility functions

tools/Models/ 
__init__.py : n/a
degmodelFinal.py           : Model of PER/CRY feedback from Hirota et al, 2012
simplified_tysonmodel.py   : Simple 2-state model of mRNA-protein oscillator
simplified_tysonmodel_2.py : Modified version of previous model with exponent=2

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