With the rotor's phase and old-young, track cell fate and drug targets at whole-genome scale.
ROTOR ANALYZER
Pick a network and task, then run. All computation runs on the server.
The Whole-Genome Rotor Analyzer is a toolset that brings the rotor computational architecture to bear on attractor analysis of gene regulatory networks. The "rotor" treats each gene's state as a twofold composite of phase (yin-yang / group / reversible) and old-young (strong-weak / semigroup / irreversible) — precisely the two primitives of all finite computation in the Krohn–Rhodes sense. Building on this, it replaces the crude on/off Boolean with a four-image encoding (silent · weak · strong · saturated) that preserves the expression-strength dimension of real, graded data. More crucially, it evolves along a single trajectory and never enumerates the 2ⁿ state space — so it can track, at whole-genome scale (twenty thousand to a hundred thousand nodes), which stable fate a cell moves toward, and can perform an in-silico knockout of each gene to screen out the core control genes that actually change that fate (candidate drug targets). Rather than fitting statistical co-expression, it evolves the network dynamics directly, tackling the one gap among the four facing AI gene foundation models that is genuinely computational in nature — the collapse at whole-genome scale. Its results have been cross-validated bit-for-bit against published benchmarks: it exactly reproduces the basin distribution of the budding-yeast cell cycle (Li 2004) and the experimentally validated therapeutic targets of the T-LGL leukemia survival network.
RSVP
