We review methods of understanding cellular interactions through computation in order to guide the synthetic design of mammalian cells for translational applications, such as regenerative medicine and cancer therapies. In doing so, we argue that the challenges of engineering mammalian cells provide a prime opportunity to leverage advances in computational systems biology. We support this claim systematically, by addressing each of the principal challenges to existing synthetic bioengineering approaches—stochasticity, complexity, and scale—with specific methods and paradigms in systems biology. Moreover, we characterize a key set of diverse computational techniques, including agent-based modeling, Bayesian network analysis, graph theory, and Gillespie simulations, with specific utility toward synthetic biology. Lastly, we examine the mammalian applications of synthetic biology for medicine and health, and how computational systems biology can aid in the continued development of these applications.
Keywords: systems biology, synthetic biology, mammalian cell, computational biology, regenerative medicine, gene circuits, signaling network, multiscale modeling
Citation: Rekhi R and Qutub AA (2013) Systems approaches for synthetic biology: a pathway toward mammalian design. Front. Physiol. 4:285. doi:10.3389/fphys.2013.00285
Received: 25 April 2013; Accepted: 19 September 2013;
Published online: 09 October 2013.
Edited by:John J. Rice, Functional Genomics and Systems Biology, USA
Reviewed by:John J. Rice, Functional Genomics and Systems Biology, USA
Copyright © 2013 Rekhi and Qutub. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Amina A. Qutub, Department of Bioengineering, Rice University, MS-142, 6100 Main Street, Houston TX 77005-1892, USA e-mail: email@example.com