Name | Modified | Size | Downloads / Week |
---|---|---|---|
Additional_scripts_and_result_files_PDGF_signalling_study.zip | 2015-09-24 | 30.5 MB | |
readme.txt | 2015-05-24 | 2.0 kB | |
optPBN_stand_alone_v2.2.3.zip | 2015-05-24 | 2.6 MB | |
optPBN_grid_based_v2.2.3.zip | 2015-05-24 | 667.6 MB | |
optPBN_stand_alone_v2.2.2.zip | 2015-05-24 | 2.6 MB | |
optPBN_stand_alone_v2.2.1.zip | 2015-05-24 | 2.6 MB | |
optPBN_stand_alone_v2.1.1.zip | 2014-11-27 | 2.6 MB | |
optPBN_stand_alone_v2.1.zip | 2014-05-05 | 41.1 MB | |
optPBN_grid_based_v2.1.zip | 2014-05-05 | 329.1 MB | |
Additional_Result_Files.zip | 2014-05-05 | 10.1 MB | |
optPBN_stand_alone_v2.0.zip | 2014-03-13 | 41.2 MB | |
optPBN_grid_based_v2.0.zip | 2014-03-13 | 332.6 MB | |
optPBN_grid_based_v1.0.zip | 2013-10-25 | 325.6 MB | |
optPBN_stand_alone_v1.0.zip | 2013-10-25 | 39.9 MB | |
Totals: 14 Items | 1.8 GB | 0 |
==================== optPBN release note ==================== Last update: Sunday 24th May 2015 Most recent version: v2.2.3 ============= optPBN v2.2.3 ============= - Stable pipeline to define the qualitative boundary of parameters with 4 types of flags in the rules as follows: 1) 'C' = constant -> fixed parameter value, e.g. for inputs 2) 'D' = default -> varied parameter value between the range of 0 to 1 3) 'L' = low -> varied parameter value lower than the counter part 'H', will mostly fall below 0.5 (adjustable) 4) 'H' = high -> varied parameter value higher than the counter part 'L', will mostly fall above 0.5 (adjutsable) ============= optPBN v2.2.2 ============= - Second effort to define the qualitative boundary of parameters with actual number in the rules e.g., rules=A+B,'1','LB','UB' ============= optPBN v2.2.1 ============= - Initial effort to manuallyn set qualitative boundary of parameters (cij) =========== optPBN v2.2 =========== - Integrate Chi-square calculation into the pipeline as another formula to make use of SD value to calculate fitting cost =========== optPBN v2.1 =========== - Major revision on the approximation of steady-state probability: applied Two-state Markov chain approach (marginal distribution) - Fixed wrong Two-state Markov chain equations in the original articles - Remove the first version of pbnStationary script (TS) and use only the second version (TS2 -> TS) - Condense the installation package, especially the SBtoolbox2 (include only the optimisation toolbox) -> from 100+MB -> 3MB =========== optPBN v2.0 =========== - Bugs fixed and improved speed of computational pipeline, especially on the grid-based pipeline =========== optPBN v1.0 =========== - Approximate steady-state distribution in multiple runs with random initial condition (no perturbation) - 2 version of pbnStationary distribution for n<25 (TS) to calculate pmf and n>25 (TS2) to calculate pdf