Statistical Model for Biochemical Network Inference
نویسندگان
چکیده
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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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 pr...
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چکیده ندارد.
15 صفحه اولCausal network inference using biochemical kinetics
MOTIVATION Networks are widely used as structural summaries of biochemical systems. Statistical estimation of networks is usually based on linear or discrete models. However, the dynamics of biochemical systems are generally non-linear, suggesting that suitable non-linear formulations may offer gains with respect to causal network inference and aid in associated prediction problems. RESULTS W...
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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 systems biology devoted to the identification of biochemical networks from experimental data. Common to both areas of research is their focus on the maximization of information gathered from experimentati...
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ژورنال
عنوان ژورنال: Communications in Statistics - Simulation and Computation
سال: 2013
ISSN: 0361-0918,1532-4141
DOI: 10.1080/03610918.2011.633200