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Systems Engineering Research, Department of Engineering Science, University of Oxford: Biological Systems

Systems Engineering Research

Environmental and Biological Systems Engineering

Biological Systems

Research this area represents applications of multiscale modelling, which is a modelling approach that combines models of different scales of a system in order to obtain an overall model of desired quality or computational efficiency which is difficult to achieve by a single scale model. This modelling paradigm is widely regarded as a promising and powerful tool in various disciplines, including process engineering, material science, computational mechanics, system biology, and biomedical engineering. Our previous work has attempted to address the common conceptual, numerical and software implementation challenges for developing multiscale models. We are now interested in applying multiscale modelling and analysis in specific areas to facilitate systems understanding and optimisation. In particular, we are developing multiscale approaches to the analysis and design of biological systems that take into account phenomena and mechanisms at sub-cellular, cellular, cell population and bio-reactor scales. Current studies include work on both micro-organisms based engineering systems and stem cells expansion and differentiation.

 

Selected Publications

Zeng, H., & Yang, A. (2020). Bridging substrate intake kinetics and bacterial growth phenotypes with flux balance analysis incorporating proteome allocation. Scientific Reports, 10(1). doi:10.1038/s41598-020-61174-0

Yang, Z., & Yang, A. (2020). Modelling the impact of operating mode and electron transfer mechanism in microbial fuel cells with two-species anodic biofilm. Biochemical Engineering Journal, 158, 107560. doi:10.1016/j.bej.2020.107560

Wu, S., Liu, J., Liu, C., Yang, A., & Qiao, J. (2019). Quorum sensing for population-level control of bacteria and potential therapeutic applications.. Cellular and molecular life sciences : CMLS. doi:10.1007/s00018-019-03326-8

Zeng, H. and Yang, A. (2019). Quantification of proteomic and metabolic burdens predicts growth retardation and overflow metabolism in recombinant Escherichia coli . Biotechnology and Bioengineering. doi:10.1002/bit.26943

Di S, Yang A. (2019). Analysis of productivity and stability of synthetic microbial communities. J. R. Soc. Interface 16:20180859. http://dx.doi.org/10.1098/rsif.2018.0859

Di, S., & Yang, A. (2018). Overyielding potential of microalgal polyculture with complementary light absorption spectra: A model-based analysis. BIOMASS & BIOENERGY, 118, 141-148. doi:10.1016/j.biombioe.2018.08.010

Bo Zhang, Hua Ye and Aidong Yang (2018). Mathematical modelling of interacting mechanisms for hypoxia mediated cell cycle commitment for Mesenchymal stromal cells. BMC Systems Biology. https://doi.org/10.1186/s12918-018-0560-3

Huang, Z., Odeleye, A. O. O., Ye, H., Cui, Z., Yang, A. (2018). Fluid dynamic characterization of a fluidized-bed perfusion bioreactor with CFD-DEM simulation. Journal of Chemical Technology and Biotechnology. https://doi.org/10.1002/jctb.5576

A. Yang (2013). On the common conceptual and computational frameworks for multiscale modeling. Industrial and Engineering Chemistry Research, 52: 11451-11459. http://dx.doi.org/10.1021/ie303123s

Y. Zhao, C. Jiang, A. Yang (2012). Towards computer-aided multiscale modelling: a generic supporting framework for model realisation and execution. Computers & Chemical Engineering, 40, 45-57. http://dx.doi.org/10.1016/j.compchemeng.2012.02.012

Y. Zhao, C. Jiang, A. Yang (2012). Towards computer-aided multiscale modelling: an overarching methodology and support of conceptual modelling. Computers & Chemical Engineering, 36, 10-21. http://dx.doi.org/10.1016/j.compchemeng.2011.06.010

A. Yang (2011). Modelling and Evaluation of CO2 Supply and Utilisation in Algal Ponds. Industrial & Engineering Chemistry Research, 50, 11181-11192. http://dx.doi.org/10.1021/ie200723w

A. Yang, W. Marquardt (2009). An ontological conceptualization of multiscale models. Computers & Chemical Engineering, 33, 822-837. http://dx.doi.org/10.1016/j.compchemeng.2008.11.015