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An automated procedure for the extraction of metabolic network information from time series data

An automated procedure for the extraction of metabolic network information from time series data

Journal of Bioinformatics and Computational Biology 4(3): 665-691

Novel high-throughput measurement techniques in vivo are beginning to produce dense high-quality time series which can be used to investigate the structure and regulation of biochemical networks. We propose an automated information extraction procedure which takes advantage of the unique S-system structure and supports model building from time traces, curve fitting, model selection, and structure identification based on parameter estimation.

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Accession: 011748578

Download citation: RISBibTeXText

PMID: 16960969

DOI: 10.1142/S0219720006002259

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