JAK-STAT signaling as a Boolean network

Boolean network derived from module 13 variables · 15 signed edges modules/jak_stat_signaling.yaml

The module's connections read as a signed regulatory graph and translated by ai-gene-review module-to-bnet. Each negative regulator is wired where the module says it acts: SOCS and the phosphatases on JAK, the phosphatases and PIAS on nuclear STATs. STAT transcription carries activation_logic because ERK serine phosphorylation of STATs only tunes maximal transcription, so it is declared an omitted regulator. In every scenario the phosphatase, PIAS and JAK-independent STAT inputs are held off unless stated.

Boxes are steps of the moduleEach is either ON (filled) or OFF. Grey arrows activate; orange flat-headed lines inhibit.
Pick a scenario, press RunSteps switch one at a time, at random, whenever their inputs say they should: the asynchronous update.
Click a box to lock itCycle free → locked ON → locked OFF, to knock a step out or force it on. The read-out updates at once.
Where it ends upEvery possible end state is computed exhaustively. One steady state, or a cycle that never settles: in a Boolean model, a transient pulse.

Scenarios curated in the module, checked in validation

Wiring

ON OFF locked input activates inhibits removed in scenario asserted, not in the rule

Where it ends up

Timeline one column per update, newest on the right

Update rules

Generated from the module's connections. A step is ON when any activator is ON and no inhibitor is (the default), unless the module declares activation_logic for it. A regulator that logic deliberately leaves out (omitted_regulators, a modulator rather than a switch) stays in the graph as a faint dotted edge and is named beside the rule.

BoolNet (.bnet) export
Download .bnet