title: Mining HIV dynamics using independent component analysis.
abstract: BACKGROUND
  We implement a data mining technique based on the method of Independent Component Analysis (ICA) to generate reliable independent data sets for different HIV therapies. We show that this technique takes advantage of the ICA power to eliminate the noise generated by artificial interaction of HIV system dynamics. Moreover, the incorporation of the actual laboratory data sets into the analysis phase offers a powerful advantage when compared with other mathematical procedures that consider the general behavior of HIV dynamics.
  
  
  RESULTS
  The ICA algorithm has been used to generate different patterns of the HIV dynamics under different therapy conditions. The Kohonen Map has been used to eliminate redundant noise in each pattern to produce a reliable data set for the simulation phase. We show that under potent antiretroviral drugs, the value of the CD4+ cells in infected persons decreases gradually by about 11% every 100 days and the levels of the CD8+ cells increase gradually by about 2% every 100 days.
  
  
  BACKGROUND
  Executable code and data libraries are available by contacting the corresponding author.
  
  
  METHODS
  Mathematica 4 has been used to simulate the suggested model. A Pentium III or higher platform is recommended.
authors.affiliation: Department of Computer Science, Wayne State University, IA, USA.
authors.forename: Sorin
authors.initials: S
authors.lastname: Draghici
authors.forename: Frank
authors.initials: F
authors.lastname: Graziano
authors.forename: Samira
authors.initials: S
authors.lastname: Kettoola
authors.forename: Ishwar
authors.initials: I
authors.lastname: Sethi
authors.forename: George
authors.initials: G
authors.lastname: Towfic
mesh_terms: D000465:Algorithms; D015496:CD4-Positive T-Lymphocytes / Q000276:immunology / Q000821:virology; D018414:CD8-Positive T-Lymphocytes / Q000276:immunology / Q000821:virology; D003198:Computer Simulation; D003628:Database Management Systems; D006678:HIV / Q000187:drug effects / Q000276:immunology; D015658:HIV Infections / Q000188:drug therapy* / Q000235:genetics / Q000276:immunology* / Q000503:physiopathology; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated; D025341:Principal Component Analysis; D016896:Treatment Outcome; D019562:Viral Load / Q000379:methods