Shmulevich, I., & Kauffman, S. A. (2004). Activities and sensitivities in Boolean network models. Physical Review Letters, 93(4), 48701–1. http://doi.org/10.1103/PhysRevLett.93.048701
1) The sensitivity of a Boolean function f on state vector x is the number of Hamming neighbors of x on which the function value is different than on x. This should be straightforward to implement for synchronous networks.
2) The average sensitivity is defined by taking the expectation of the sensitivity with respect to a distribution over states x. A simple case would be the uniform distribution, though we will want to support arbitrary distributions as well (say, from a cyclic attractor, or along a biologically relevant trajectory).
bcdaniels
commented
7 years ago
As defined in
Shmulevich, I., & Kauffman, S. A. (2004). Activities and sensitivities in Boolean network models. Physical Review Letters, 93(4), 48701–1. http://doi.org/10.1103/PhysRevLett.93.048701
1) The sensitivity of a Boolean function f on state vector x is the number of Hamming neighbors of x on which the function value is different than on x. This should be straightforward to implement for synchronous networks. 2) The average sensitivity is defined by taking the expectation of the sensitivity with respect to a distribution over states x. A simple case would be the uniform distribution, though we will want to support arbitrary distributions as well (say, from a cyclic attractor, or along a biologically relevant trajectory).