Sentence examples for interacting reactions from inspiring English sources

Furthermore, in this article we define detailed node and edge annotations that allow for an analysis of each pathway with respect to its core genetic dependencies and can scale up to include an analysis of interacting reactions, compounds and KEGG sub-networks.

A simple model is proposed for predicting and/or correlating the overall behavior of a large number of noninteracting or interacting reactions.

First, comparisons across different metabolic states can identify conserved modules comprising robustly interacting reactions that may be co-regulated by a common allosteric effector.

Furthermore, we define detailed node and edge annotations, which enable us to track each pathway, not only with respect to its genetic dependencies, but also allow for an analysis of the interacting reactions, compounds and KEGG sub-networks.

In fact, knockout solutions that lead to improved phenotypes regarding the production of succinic acid are not straightforward to identify since they involve a considerable number of interacting reactions.

This makes the technique particularly attractive in biomedicine, where a phenotype can be the result of many interacting reactions and detailed kinetic information for each enzyme involved under disease conditions is unavailable and difficult to obtain experimentally.

The few bits of information required by this assumption could be introduced into cortex through interacting reaction-diffusion systems (e.g., Turing 1952; Roth et al. 2007), by chemically defining regions of nonpatchy connectivity and longer projections.

Models which apply to parallel interacting and non-interacting reactions, for all industrially relevant reaction regimes must be developed and validated against experimental measurements.

Formally, a reaction graph G is a bipartite directed graph, that is a triple G = (S, R, A), where S is the set of species nodes, R is the set of reaction nodes, and A ⊆ S × R ∪ R × S the set of arcs that describes how species interact through reactions.

The SSA simulates a system of biochemical reactions with N species and M reactions, interacting inside a fixed volume V at constant temperature.

Hence, the coarse-grained version of the full network (14) is simply (17) → k in S → k ′ P. Note that the deterministic QSSA has reduced our network from one with 5 species interacting via 7 elementary reactions, reaction scheme (14), to one with 2 species interacting via 2 reactions, one elementary and one non-elementary, reaction scheme (17).