@article{LAUBENBACHER2004523,
    Abstract = {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 of states for each of the variables. The simplest examples of such models are Boolean networks, in which variables have only two possible states. The use of a larger number of possible states allows a finer discretization of experimental data and more than one possible mode of action for the variables, depending on threshold values. Furthermore, with a suitable choice of state set, one can employ powerful tools from computational algebra, that underlie the reverse-engineering algorithm, avoiding costly enumeration strategies. To perform well, the algorithm requires wildtype together with perturbation time courses. This makes it suitable for small to meso-scale networks rather than networks on a genome-wide scale. An analysis of the complexity of the algorithm is performed. The algorithm is validated on a recently published Boolean network model of segment polarity development in Drosophila melanogaster.},
    Author = {Laubenbacher, Reinhard and Stigler, Brandilyn},
    File = {A computational algebra approach to the reverse engineering of gene regulatory networks - j.jtbi.2004.04.037 - a - q.pdf},
    ISSN = {0022-5193},
    Journal = {Journal of Theoretical Biology},
    Keywords = {Reverse engineering, Gene regulatory networks, Discrete modeling, Computational algebra},
    Number = {4},
    Pages = {523 - 537},
    Title = {A computational algebra approach to the reverse engineering of gene regulatory networks},
    URL = {http://www.sciencedirect.com/science/article/pii/S0022519304001754},
    Volume = {229},
    Year = {2004},
    bdsk-url-1 = {http://www.sciencedirect.com/science/article/pii/S0022519304001754},
    bdsk-url-2 = {https://doi.org/10.1016/j.jtbi.2004.04.037},
    date-added = {2021-01-20 18:39:05 +0100},
    date-modified = {2021-01-20 18:39:05 +0100},
    doi = {10.1016/j.jtbi.2004.04.037}
}

@article{LAUBENBACHER2004523, Abstract = {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 of states for each of the variables. The simplest examples of such models are Boolean networks, in which variables have only two possible states. The use of a larger number of possible states allows a finer discretization of experimental data and more than one possible mode of action for the variables, depending on threshold values. Furthermore, with a suitable choice of state set, one can employ powerful tools from computational algebra, that underlie the reverse-engineering algorithm, avoiding costly enumeration strategies. To perform well, the algorithm requires wildtype together with perturbation time courses. This makes it suitable for small to meso-scale networks rather than networks on a genome-wide scale. An analysis of the complexity of the algorithm is performed. The algorithm is validated on a recently published Boolean network model of segment polarity development in Drosophila melanogaster.}, Author = {Laubenbacher, Reinhard and Stigler, Brandilyn}, File = {A computational algebra approach to the reverse engineering of gene regulatory networks - j.jtbi.2004.04.037 - a - q.pdf}, ISSN = {0022-5193}, Journal = {Journal of Theoretical Biology}, Keywords = {Reverse engineering, Gene regulatory networks, Discrete modeling, Computational algebra}, Number = {4}, Pages = {523 - 537}, Title = {A computational algebra approach to the reverse engineering of gene regulatory networks}, URL = {http://www.sciencedirect.com/science/article/pii/S0022519304001754}, Volume = {229}, Year = {2004}, bdsk-url-1 = {http://www.sciencedirect.com/science/article/pii/S0022519304001754}, bdsk-url-2 = {https://doi.org/10.1016/j.jtbi.2004.04.037}, date-added = {2021-01-20 18:39:05 +0100}, date-modified = {2021-01-20 18:39:05 +0100}, doi = {10.1016/j.jtbi.2004.04.037} }