Algebraic Statistical Model for Biochemical Network Inference
نویسندگان
چکیده
We describe a statistical method for predicting most likely reactions in a biochemical reaction network from the longitudinal data on species concentrations. Such data is relatively easily available in biochemical laboratories, for instance, via the popular RTPCR technology. Under the assumed kinetics of the law of mass action, we also propose the data-based procedures for (i) estimating the prediction errors and (ii) network dimension reduction. The algorithm in (ii) allows in particular for the application of the original algebraic inferential procedure described in [3] without the unnecessary restrictions on the dimension of the network stoichiometric space. Simulated examples of biochemical networks are analyzed in order to assess the proposed methods’ performance.
منابع مشابه
Statistical Model for Biochemical Network Inference
We describe a statistical method for predicting most likely reactions in a biochemical reaction network from the longitudinal data on species concentrations. Such data is relatively easily available in biochemical laboratories, for instance, via the popular RT-PCR technology. Under the assumed kinetics of the law of mass action, we also propose the data-based algorithms for estimating the predi...
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تاریخ انتشار 2011