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In fact, although the kinetic parameters are important to determine the dynamical behavior, a circuit topology by itself can determine or constrain the dynamics and provide structural sources of robustness [19] [21] or noise tolerance [32].
These sources of robustness may be particularly important given ubiquitous and substantial stochastic variation in protein copy number [ 50].
Studying the dynamic patterns of biological processes helps identify control points, modules and sources of robustness [ 5].
A number of different sources of robustness in cellular function and biochemical networks are discussed in the literature (see e.g. [ 35, 36]).
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This had already been a frequently observed issue during the public services tests and a major source of robustness issues.
It is important to emphasize that the proposed mutation rules are quite extensive and try to focus on testing limit conditions that are typically the source of robustness problems.
An important aspect is that these rules must be focused on limit conditions that typically represent difficult validation aspects (which are typically the source of robustness problems), such as: Null and empty values (e.g., null string, empty string).
Based on this general description of probe input, we propose a set of rules (Table 1), which have been defined based on previous works on robustness testing [18, 20, 26], and explore limit conditions that are typically the source of robustness problems.
Degeneracy is a fundamental source of biological robustness, complexity and evolvability in many biological systems.
A recent study of the biochemical reaction networks reveals the structural sources of the cellular robustness[ 23].
However through iterative cross comparisons of multiple data sources, the robustness of our findings were strengthened.
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