BioCAE: A New Strategy of Complex Biological Systems for Biofabrication of Tissues and OrgansDernowsek JA1,2*, Rezende RA1,2,3 and JVL da Silva1,2
- *Corresponding Author:
- Janaina de Andrea Dernowsek
Center for information technology Renato Archer (CTI)
3D Technologies Research Group (NT3D)
E-mail: [email protected]
Received date: April 29, 2017; Accepted date: June 07, 2017; Published date: June 17, 2017
Citation: Dernowsek JA, Rezende RA, da Silva JVL (2017) BioCAE: A New Strategy of Complex Biological Systems for Biofabrication of Tissues and Organs. J Tissue Sci Eng 8:200. doi:10.4172/2157-7552.1000200
Copyright: © 2017 Dernowsek JA, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Biofabrication as an interdisciplinary area is fostering new knowledge and integration of areas like nanotechnology, chemistry, biology, physics, materials science, control systems, among many others, necessary to accomplish the challenge of bioengineering functional complex tissues. The emergence of integrated platforms and systems biology to understand complex biological systems in multiscale levels will enable the prediction and creation of biofabricated biological structures. This systematic analysis (meta-analysis) or integrated platforms for estimating biological process have been named as BioCAE, which will become the key for important steps of the biofabrication processes. Biological Computational Aided Engineering (BioCAE) is a new computational approach to understanding and bioengineer complex tissues (biofabrication) using a combination of different methods as multiscale modelling, computer simulations, data mining and systems biology. In addition, multi-agent systems (MAS), which are composed of different interacting computing entities called agents, also provide an interesting way to design and implement simulations of biological systems, integrating them with all steps of the BioCAE. MAS as a part of computational science have become a growing area to manipulate and solve complex problems. This paper presents an approach that will allow predicting the development and behavior of different biological processes such as molecular networks, gene interactions, cells, tissues and organs due to its flexibility, beyond to provide a new outlook in the biofabrication of tissues and organs.