Graph diffusion using a Markov random walk
A Markov Random Walk takes an inital distribution
p0 and calculates the stationary distribution of that.
The diffusion process is regulated by a restart probability
r which controls how often the MRW jumps back to the initial values.
random.walk(p0, graph, r = 0.5, ...)
a scalar between (0, 1). restart probability if a Markov random walk with restart is desired
returns the stationary distribution as numeric vector
Simon Dirmeier, email@example.com
Tong, H., Faloutsos, C., & Pan, J. Y. (2006),
Fast random walk with restart and its applications.
Koehler, S., Bauer, S., Horn, D., & Robinson, P. N. (2008), Walking the interactome for prioritization of candidate disease genes. The American Journal of Human Genetics
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