Computational dynamic modeling of complex regulatory networks is essential for the discovery of new capabilities of biological systems and prediction of specific perturbations that result in desired outcomes.
There is a growing interest in developing synthetic materials with self-assembly capability since it is a symbol of biological systems.
As it is easy to imagine this capability has enhanced tremendously our understanding of biological systems.
Our capabilities for systematic design and engineering of biological systems are rapidly increasing.
We use the term biosimulation model to describe a mathematical abstraction that is intended to represent the structure, functions, capabilities and qualities of a class of biological systems.
Mazur, P. Cryobiology: the freezing of biological systems.
Spatial patterning is a ubiquitous feature of biological systems.
Synthetic biology involves the creation of biological systems for new applications by modifying and reassembling biological components.
Biological sciences will continue to be significant, as fundamental scientific research will improve our understanding of biological systems and support complex data science systems.
Robustness, intended as the capability to cope with fluctuations of the molecular species concentrations, caused by endogenous and exogenous perturbations, and to preserve biological functions despite inter-individual variability of kinetic parameters, is a key feature of biological systems.
Adopting these capabilities to biological system design should allow engineers to use previously created solutions and apply them to solve novel problems.
