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2017 ; 18
(Suppl 2
): 24
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PRODIGEN: visualizing the probability landscape of stochastic gene regulatory
networks in state and time space
#MMPMID28251874
Ma C
; Luciani T
; Terebus A
; Liang J
; Marai GE
BMC Bioinformatics
2017[Feb]; 18
(Suppl 2
): 24
PMID28251874
show ga
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.