Intelligent Computing Lab.
GeNOSA - Integrated Platform for Gene Regulatory Networks

GeNOSA: Inferring and Experimentally Supporting Quantitative Gene Regulatory Networks in Prokaryotes

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This package included several tools to perform reconstruction of gene regulatory networks from microarray data and connectivity information.


GeNOSA package

Usage of parameters

Optimal NCA for GRNs v1.2.13
Usage: OptNCA [options] 
-h: Display this help.

[Input data parameters]
-P: Pass symbols.
-a: Maximum value of each gene. (Default: 10)
-b: Minimum value of each gene. (Default: -10)
-c: Input file of control strenth.  (Default: CS.txt)
-C: Compare to input file of control strenth.  (Default: CS0.txt)
-e: Input file of expression profiles. (Default: E.txt)
-t: Input file of transcription factors activities. (Default: TFA.txt)
-T: Compare to input file of transcription factors activities. (Default: TFA0.txt)
-F: Fitness function for optimization. (Default: 0)
    0 : Least Square Error
    1 : Root Mean Square Error
    2 : Model Error

[Perturbation parameters]
-s: The standard deviation of perturbation copies. (Default: 0.5)
-m: Perturbation handler. (Default: 0)
    0 : None
    1 : Read
    2 : Export
-n: The number of perturbation copies. (Default: 20, Maximum: 50)
-N: Using pre-defined perurbation set. (Default: E%02d.txt)
-x: Optimization stretegy.  (Default: 1)
    1 : optimize TFA only
    2 : optimize TFA and CS (no constraints)
    3 : optimize TFA and CS (with loose constraints)
    4 : optimzie TFA and CS (with tight constraints)
-v: Message verbose level from simple to verbose: 0->9 (Default: 0)

[Post-processing parameters]
-M: Post process for analysis. (Default: 0)
    0 : None
    1 : LSE
    2 : CS difference
    3 : TFA standard deviation
    4 : Overall mean from data
-I: Input pattern. (Default: IN%02d.txt)

[OSA parameters]
-i: OSA initial temperature. (Default: 1000)
-r: OSA cooling rate. (Default: 0.999)
-u: OSA radius. (Default: 0.05)
-S: Steps to run. (Default: 1000)


Synthetic datasets

Experimental datasets

Related publications

Contact Information

EMail: Yi-Hsiung Chen and Hsinn-Ying Ho