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Multivariate predictive mathematical models for biochemical recurrence after radical prostatectomy by decreasing sample size and time to clinical outcomes maximize trial efficiency and identify the patients most likely to benefit from secondary prevention.
To develop nonlinear state-space models for biochemical networks requires identifying the variables, their components and biochemical reactions which characterize dynamics of the biochemical networks.
Kinetic models have been widely used mechanistic models for biochemical networks and hence should be the basis of mathematic models of biochemical networks.
We took the recent formulation of kinetic models for biochemical networks in which the derivatives of the concentrations of the compounds in the network are decomposed into the product of the stoichiometrix matrix and vector of the reaction rates [37].
Dynamic models for biochemical
In the report, we demonstrated that the presented nonlinear state-space models for biochemical networks that consist of systems and observation equations not only can deal with both hidden and observed variables, but also can cover both deterministic and random variables.
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A Cox model for biochemical failure was constructed and shown as the "Initial Cox" column in Table 3.
The silkworm is the best-characterized model for biochemical, genetic, and genomic studies of the order Lepidoptera, and for insect domestication.
However, skin fibroblasts produce the α3 but not the α6 chain (unpublished personal data), thus today, a cell model for biochemical investigation is lacking.
The present study was designed to assess the effect of two doses of deltamethrin on several biochemical parameters on serum and tissues of catfish (Clarias gariepinus) to establish this species as a model for biochemical studies.
In 1997, a group of surgeons at Northwestern University who had noticed that surgical scars in rabbit ears remained elevated months after wounding standardized a rabbit ear model for biochemical and molecular scarring studies.
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