title: PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space.
abstract: BACKGROUND
  Visualizing the complex probability landscape of stochastic gene regulatory networks can further biologists' understanding of phenotypic behavior associated with specific genes.
  
  
  RESULTS
  We present PRODIGEN (PRObability DIstribution of GEne Networks), a web-based visual analysis tool for the systematic exploration of probability distributions over simulation time and state space in such networks. PRODIGEN was designed in collaboration with bioinformaticians who research stochastic gene networks. The analysis tool combines in a novel way existing, expanded, and new visual encodings to capture the time-varying characteristics of probability distributions: spaghetti plots over one dimensional projection, heatmaps of distributions over 2D projections, enhanced with overlaid time curves to display temporal changes, and novel individual glyphs of state information corresponding to particular peaks.
  
  
  CONCLUSIONS
  We demonstrate the effectiveness of the tool through two case studies on the computed probabilistic landscape of a gene regulatory network and of a toggle-switch network. Domain expert feedback indicates that our visual approach can help biologists: 1) visualize probabilities of stable states, 2) explore the temporal probability distributions, and 3) discover small peaks in the probability landscape that have potential relation to specific diseases.
authors.affiliation: Electronic Visualization Laboratory, Department of Computer Science, University of Illinois at Chicago, 851 S. Morgan St (M/C 152), Room 1120 SEO, Chicago, 60607, IL, US. cma6@uic.edu.
authors.forename: Chihua
authors.initials: C
authors.lastname: Ma
authors.affiliation: Electronic Visualization Laboratory, Department of Computer Science, University of Illinois at Chicago, 851 S. Morgan St (M/C 152), Room 1120 SEO, Chicago, 60607, IL, US.
authors.forename: Timothy
authors.initials: T
authors.lastname: Luciani
authors.affiliation: Department of Bioengineering, University of Illinois at Chicago, 851 S. Morgan St (M/C 063), Room 218 SEO, Chicago, 60607, IL, USA.
authors.forename: Anna
authors.initials: A
authors.lastname: Terebus
authors.affiliation: Department of Bioengineering, University of Illinois at Chicago, 851 S. Morgan St (M/C 063), Room 218 SEO, Chicago, 60607, IL, USA.
authors.forename: Jie
authors.initials: J
authors.lastname: Liang
authors.affiliation: Electronic Visualization Laboratory, Department of Computer Science, University of Illinois at Chicago, 851 S. Morgan St (M/C 152), Room 1120 SEO, Chicago, 60607, IL, US.
authors.forename: G Elisabeta
authors.initials: GE
authors.lastname: Marai
mesh_terms: D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D016208:Databases, Factual; D053263:Gene Regulatory Networks; D020407:Internet; D008958:Models, Molecular; D011336:Probability; D011487:Protein Conformation; D012984:Software; D013269:Stochastic Processes; D014158:Transcription, Genetic
keywords: Feature detection and tracking; Modelling/Simulation; Network analysis; Systems biology