Griffin: A Tool for Symbolic Inference of Synchronous Boolean Molecular Networks.

ABSTRACT: Boolean networks are important models of biochemical systems, located at the high end of the abstraction spectrum. A number of Boolean gene networks have been inferred following essentially the same method. Such a method first considers experimental data for a typically underdetermined "regulation" graph. Next, Boolean networks are inferred by using biological constraints to narrow the search space, such as a desired set of (fixed-point or cyclic) attractors. We describe Griffin, a computer tool enhancing this method. Griffin incorporates a number of well-established algorithms, such as Dubrova and Teslenko's algorithm for finding attractors in synchronous Boolean networks. In addition, a formal definition of regulation allows Griffin to employ "symbolic" techniques, able to represent both

SUBMITTER: Munoz S 

PROVIDER: S-EPMC5845696 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature