Parameter estimation for Boolean models of biological networks (2009)
Dimitrova, Elena, Garcia-Puente, Luis David, Hinkelmann, Franziska, Jarrah, Abdul S., Laubenbacher, Reinhard, Stigler, Brandilyn, ...
Boolean networks have long been used as models of molecular networks and play an increasingly important role in systems biology. This paper describes a software package, Polynome, offered as a web...
Network Topology as a Driver of Bistability in the lac Operon (2008)
Stigler, Brandilyn, Veliz-Cuba, Alan
The lac operon in Escherichia coli has been studied extensively and is one of the earliest gene systems found to undergo both positive and negative control. The lac operon is known to exhibit...
Design of experiments and biochemical network inference (2007)
Laubenbacher, Reinhard, Stigler, Brandilyn
Design of experiments is a branch of statistics that aims to identify efficient procedures for planning experiments in order to optimize knowledge discovery. Network inference is a subfield of...
Efficiently computing Groebner bases of ideals of points (2007)
Just, Winfried, Stigler, Brandilyn
We present an algorithm for computing Groebner bases of vanishing ideals of points that is optimized for the case when the number of points in the associated variety is less than the number of...
Computing Groebner bases of ideals of few points in high dimensions (2006)
Just, Winfried, Stigler, Brandilyn
A contemporary and exciting application of Groebner bases is their use in computational biology, particularly in the reverse engineering of gene regulatory networks from experimental data. In this...
Reverse-engineering of polynomial dynamical systems (2006)
Jarrah, Abdul Salam, Laubenbacher, Reinhard, Stigler, Brandilyn, Stillman, Michael
Multivariate polynomial dynamical systems over finite fields have been studied in several contexts, including engineering and mathematical biology. An important problem is to construct models of such...
A Computational Algebra Approach to the Reverse Engineering of Gene Regulatory Networks (2003)
Laubenbacher, Reinhard, Stigler, Brandilyn
This paper proposes a new method to reverse engineer gene regulatory networks from experimental data. The modeling framework used is time-discrete deterministic dynamical systems, with a finite set...