These scripts demonstrate the use of bayesian metamodeling of complex biological systems across varying representations.
Authors: Liping Sun, Barak Raveh
License:
Publications:
- matlab: The scripts are built upon and work with Matlab.
- bnt: Bayes Net Toolbox for Matlab.
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Either use the bnt version here (under bnt_master/), or download a recent version of bnt here: https://github.com/bayesnet/bnt.
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If downloaded, apply two minor bugfixes on bnt:
- Disable line 132 of /Your-Path-To/bnt-master/BNT/learning/learn_params_dbn_em.m.
125- loglik = 0; 126- for l=1:length(cases) 127- evidence = cases{l}; 128- if ~iscell(evidence) 129- error('training data must be a cell array of cell arrays') 130- end 131- [engine, ll] = enter_evidence(engine, evidence); 132- % assert(~isnan(ll)) 133- loglik = loglik + ll; 134- T = size(evidence, 2);
- Wrap line 85 with the following if statement in /Your-Path-To/bnt-master/BNT/general/mk_bnet.m.
85- if length(mems)>=1 86- bnet.rep_of_eclass(e) = mems(1); 87- end
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Add the path of the bnt package:
1- addpath(genpathKPM('/Your-Path-To/bnt-master'))
data
contains the data of six input models and the metamodel including:- JSON files with the values of model parameters and variables:
GI.dat
with the observed values for the glucose intake after a mealGb_kt_input_err101.dat
andGb_kt_input_sigma101.dat
with the input values for different accuracy and precision of model variables G_B and kt072919-INS1e-30min-Enrichment-analysis-cleaned-summary.xlsx
with the data for the metabolism model
scripts
contains all the bnet scripts for metamodeling, please refer to README.md inscripts
for more detailsbnt_master
contains Bayes Net Toolbox for Matlab with the bugfixes.