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For Researchers · PageRank

PageRank for a gene network

Built for researchers prototyping or validating an idea. Prototype fast, reproduce exactly, and share a citable, interactive version of your model. Simulate a gene network live below — adjust the inputs and watch it respond, right in your browser.

PageRankLive

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PageRank ranks nodes by importance: a page is important if important pages link to it. It is computed by imagining a random surfer who follows links with probability d and jumps randomly otherwise, then finding where they spend the most time. This eigenvector of the link matrix launched Google and now ranks everything from proteins to social influence.

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Data Inspector

Damping0.85
Top node23.6%
Methodpower iteration

Governing equation

Reading this result: PageRank is the stationary distribution of a random surfer who follows links with probability d and teleports to a random page with probability 1−d. At d=0.85 link structure dominates but teleport still keeps every node reachable.

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Frequently asked questions

Is this good for researchers?
Yes — this version of "PageRank for a gene network" is framed for researchers prototyping or validating an idea. Prototype fast, reproduce exactly, and share a citable, interactive version of your model.
Do I need to install anything?
No. It runs in any modern browser, free, with no account required.