Products

Software Packages Developed in Our Laboratory

Personalized Rx

Genet: Identifying Gene Signatures with Implication Networks

     
  1. C Environment - This gives the set of marker genes using the algorithm executing in C environment. This outputs intermediate files as well.
        Instructions | zip file
  2.  
  3. R-C Environment - This gives the set of marker genes using the algorithm executing in R-C environment. This does not output intermediate files.
        Instructions | zip file
  4.  
  5. CommonRules - This gives the set of common interactions.
        Instructions | text file temp-ones | text file temp-zeros
  6.  
  7. Ranking candidate genes with Cox model.
        Instructions | zip file
  8.  
  9. Ranking candidate genes with Random Forests.
        Instructions | zip file
  10.  
  11. Ranking candidate genes with Relief.
        Instructions | zip file
  12.  
  13. Comparison with Boolean Implication Networks
        Instructions | zip file
  14.  
  15. Comparison with Bayesian Networks
        Instructions | zip file
  16.  
  17. Comparison with Gene Association Networks based on Pearson's correlation
        Instructions | zip file

  18. Bayes Net Compare (Part 1, Part 2), BooleanNet Compare zip file

MEGPath: Identifying biologically relevant pathways matching longitudinal phenotype information in dose-response time series microarray data

        MEGPath -  zip file

Software Engineering

     
  1. Ma Y, Guo L, Cukic B. A Statistical Framework for the Prediction of Fault-Proneness. Advances in Machine Leaning Application in Software   Engineering, Idea Group Inc., 2006
        Manuscript
  2.  
  3. Guo L, Ma Y, Cukic B, Singh H. Robust Prediction of Fault-Proneness by Random Forests. Proc. 15th IEEE International Symposium on Software   Reliability Engineering (ISSRE 2004), pp.417-428, IEEE Press, 2004 (Extended paper invited by Kluwer's Empirical Software Engineering)   (Acceptance rate: 25%)
        Manuscript
  4.  
  5. Guo L, Mukhopadhyay S, Cukic B. Does Your Result Checker Really Check? Proc. the International Conference on Dependable Systems and   Networks (DSN 2004), pp.399-405, IEEE Press, 2004 (Acceptance rate: 15%)
        Manuscript
  6.  
  7. Boddu R, Guo L, Mukhopadhyay S, Cukic B. RETNA: From Requirements to Testing in a Natural Way. Proc. 12th IEEE International Requirements   Engineering Conference (RE 2004), pp.262-271, IEEE Press, 2004 (Acceptance rate: 20%)
        Manuscript
  8.  
  9. Guo L, Cukic B, Singh H. Predicting Fault Prone Modules by the Dempster-Shafer Belief Networks. Proc. 18th IEEE International Conference on Automated Software Engineering (ASE 2003), pp.249-252, IEEE Press, 2003 (Acceptance rate: 15%)
        Manuscript
  10.  
  11. Cukic B, Gunel E, Singh H, Guo L. The Theory of Software Reliability Corroboration. IEICE Transactions on Information & Systems, Vol. E86-D, No. 10, October, 2003
        Manuscript