Bow-tie or hourglass structure is a common architectural feature found in many biological systems .
This offers a mechanism to understand a common architectural principle of biological systems , and a way to quantitate the effective rank of the goals under which they evolved.
Many biological systems show bow-tie (also called hourglass) architecture.
This offers a mechanism to understand a common architectural principle of biological systems , and a way to quan-titate the rank of the goals under Which they evolved.
Since complete absence of noise is a nonrealistic scenario in biological systems , we conclude that sum-mutations cannot account for bow-tie evolution.
The finding of such laws provides insight for how patterns emerge in stochastic mechanochemical systems, while also informing understanding and engineering of complex biological systems .
Complex biological systems consist of many parts that interact in non-obvious ways.
The method for finding a unified scaling expression using an agent-based simulation approach is extendible to describing emergent laws in a variety of similar complex biological systems .
The unified expression would greatly aid in predicting mechanisms of complex in vivo biological systems while enabling rapid prototyping of myosin-based technologies .
Our evolutionary model could be further expanded to give a more detailed representation of specific biological systems .
Such assumptions seem justifiable on the basis of the biological systems that we are interested in.
|Model Outcomes and Biological Implications|
Several biological systems are well suited to empirical exploration of this idea.
The general selection mechanism that we implement is representative of the biological systems on which our models are based; i.e.
We studied Loregic’s ability to characterize gene regulation in both small and complex biological systems .
Yeast (S. Cerevisiae) constitutes a small but well-studied biological system .
By contrast, human cancers are much more complex biological systems and we use them to illustrate how Loregic can accommodate many different types of regulators (e.g.
In our opinion, this meticulous structure of the energy landscape for our simplified model is of general interest to other cell cycle dynamics, and the proposed methods can be applied to study similar biological systems .
|Finite volume effect|
This is a reasonable assumption for most biological systems .
However, it is still difficult to quantify the robustness and adaptivity of cellular networks, even for a small cellular network perturbed by intrinsic random fluctuations, due to the massive cross regulations and nonlinear nature of such biological systems .