Reverse engineering time discrete finite dynamical systems: a feasible undertaking?

ABSTRACT: With the advent of high-throughput profiling methods, interest in reverse engineering the structure and dynamics of biochemical networks is high. Recently an algorithm for reverse engineering of biochemical networks was developed by Laubenbacher and Stigler. It is a top-down approach using time discrete dynamical systems. One of its key steps includes the choice of a term order, a technicality imposed by the use of Gröbner-bases calculations. The aim of this paper is to identify minimal requirements on data sets to be used with this algorithm and to characterize optimal data sets. We found minimal requirements on a data set based on how many terms the functions to be reverse engineered display. Furthermore, we identified optimal data sets, which we characterized using a geometric property

SUBMITTER: Delgado-Eckert E 

PROVIDER: S-EPMC2654658 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature