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Figure 11b shows the equivalent molecular pathway model of the same pathway.
A grand challenge of computational systems biology is to create a molecular pathway model of the whole cell.
Each molecular pathway model can be treated as a black box as long as we assume that system is well-mixed The inputs and outputs for each biological pathway model represent the state at times n and n + 1, respectively.
1, 10, 13, 15, 22, 26 A molecular pathway model M can be thought of as "black box" which describes the biomolecular kinetics of a set of molecular species, S M. The input to the black box are the concentrations of species at time t = n, denoted as S M, n,.
27 X o is the set of allowed inputs to the integrated or coupled model O. Y o is the set of allowed outputs of the integrated model O. D is a set of unique component references (names); in this case, it is the list of the names or references to each molecular pathway model.
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In this architecture, the whole cell, using the theoretical framework and conditions prescribed in Appendix A, can be viewed as a network of D molecular pathways as shown in Fig. 2a or modelled as an interconnected ensemble of D molecular pathway models, shown in Fig. 2b.
A set of molecular pathway models may have common species and/or duplicate reaction pathways.
The user interacts with the GUI to specify one or more molecular pathway models to be integrated.
16 Computational systems biologists translate these molecular pathways into molecular pathway models, as shown on the right in Fig. 1, which are the quantification of molecular interactions.
Current approaches involve merging smaller molecular pathway models' source codes to create a large monolithic model (computer program) that runs on a single computer.
In molecular pathway modeling, PON1 mapped as a central node in interactions predicted among all the relevant factors in the RF analysis.
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