2008/10/03 by Gheorghe Crăciun, Craciun, Gheorghe, Casian Pantea +3
Biochemistry, Genetics and Molecular Biology · Computer Science · #Applications (stat.AP) #Computational Drug Discovery Methods #FOS: Biological sciences #FOS: Computer and information sciences #Gene Regulatory Network Analysis #Microbial Metabolic Engineering and Bioproduction #Molecular Networks (q-bio.MN) #Quantitative Methods (q-bio.QM)
paper · pdf · doi:10.48550/arxiv.0810.0561
openalex publication_date 2008/10/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present a novel method for identifying a biochemical reaction network based on multiple sets of estimated reaction rates in the corresponding reaction rate equations arriving from various (possibly different) experiments. The current method, unlike some of the graphical approaches proposed in the literature, uses the values of the experimental measurements only relative to the geometry of the biochemical reactions under the assumption that the underlying reaction network is the same for all the experiments. The proposed approach utilizes algebraic statistical methods in order to parametrize the set of possible reactions so as to identify the most likely network structure, and is easily scalable to very complicated biochemical systems involving a large number of species and reactions. The method is illustrated with a numerical example of a hypothetical network arising form a "mass transfer"-type model.