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Synthetic Biology underpins advances in the bioeconomy
Biological systems - including the simplest cells - exhibit a broad range of functions to thrive in their environment. Research in the Imperial College Centre for Synthetic Biology is focused on the possibility of engineering the underlying biochemical processes to solve many of the challenges facing society, from healthcare to sustainable energy. In particular, we model, analyse, design and build biological and biochemical systems in living cells and/or in cell extracts, both exploring and enhancing the engineering potential of biology.
As part of our research we develop novel methods to accelerate the celebrated Design-Build-Test-Learn synthetic biology cycle. As such research in the Centre for Synthetic Biology highly multi- and interdisciplinary covering computational modelling and machine learning approaches; automated platform development and genetic circuit engineering ; multi-cellular and multi-organismal interactions, including gene drive and genome engineering; metabolic engineering; in vitro/cell-free synthetic biology; engineered phages and directed evolution; and biomimetics, biomaterials and biological engineering.
@article{Scholes:2017:10.1016/j.cbpa.2017.04.008,
author = {Scholes, NS and Isalan, M},
doi = {10.1016/j.cbpa.2017.04.008},
journal = {Current Opinion in Chemical Biology},
pages = {1--7},
title = {A three-step framework for programming pattern formation},
url = {http://dx.doi.org/10.1016/j.cbpa.2017.04.008},
volume = {40},
year = {2017}
}
TY - JOUR
AB - The spatial organisation of gene expression is essential to create structure and function in multicellular organisms during developmental processes. Such organisation occurs by the execution of algorithmic functions, leading to patterns within a given domain, such as a tissue. Engineering these processes has become increasingly important because bioengineers are seeking to develop tissues ex vivo. Moreover, although there are several theories on how pattern formation can occur in vivo, the biological relevance and biotechnological potential of each of these remains unclear. In this review, we will briefly explain four of the major theories of pattern formation in the light of recent work. We will explore why programming of such patterns is necessary, while discussing a three-step framework for artificial engineering approaches.
AU - Scholes,NS
AU - Isalan,M
DO - 10.1016/j.cbpa.2017.04.008
EP - 7
PY - 2017///
SN - 1879-0402
SP - 1
TI - A three-step framework for programming pattern formation
T2 - Current Opinion in Chemical Biology
UR - http://dx.doi.org/10.1016/j.cbpa.2017.04.008
UR - http://hdl.handle.net/10044/1/48030
VL - 40
ER -