Imperial College London


Faculty of Natural SciencesDepartment of Mathematics

Research Associate



a.mannan Website




6M34Huxley BuildingSouth Kensington Campus





My research interests lie at the interface between mathematics, molecular biology and synthetic biology. In particular, I have been developing mathematical models of the interplay between cell metabolism and its control by genetically encoded regulatory circuits, and use ideas from control theory to understand how interaction parameters and control circuit architecture affect the behaviour of these systems.

I am also interested in applying these models to understanding how to direct the design of synthetic genetic circuits, for applications in metabolic engineering (biochemical production) and synthetic biology.

Throughout my career I have enjoyed and benefited from working closely with experimentalists in UK, Japan and USA, and endeavour to make strong contributions to science through collaborative research.

Brief Bio:

I completed my undergraduate in MSci Mathematics from Imperial College London, and continued my interest in mathematical biology to pursue a PhD studentship in the field of Systems Biology, at the University of Surrey. The key contribution of my thesis was the construction of a kinetic model of the central carbon metabolism of E. coli. After continuing onto a short postdoc position at University of Surrey in the same area, I moved to the University of Aberdeen, UK, to pursue a postdoc where I was studying the metabolism of O. sativa (rice plant). Currently, I am a postdoc research associate in the Biomolecular control group of Dr. Diego OyarzĂșn, at the Department of Mathematics, where I am working on developing models to understand the control of cell metabolism, and how control circuit architecture and parameters affect the behaviour of these systems.



Liu D, Mannan AA, Han Y, et al., 2018, Dynamic metabolic control: towards precision engineering of metabolism., J Ind Microbiol Biotechnol

Mannan AA, Liu D, Zhang F, et al., 2017, Fundamental Design Principles for Transcription-Factor-Based Metabolite Biosensors, Acs Synthetic Biology, Vol:6, ISSN:2161-5063, Pages:1851-1859

Wu H, von Kamp A, Leoncikas V, et al., 2016, MUFINS: multi-formalism interaction network simulator., Npj Syst Biol Appl, Vol:2, ISSN:2056-7189

Weisse AY, Mannan AA, Oyarzun DA, 2016, Signaling Tug-of-War Delivers the Whole Message, Cell Systems, Vol:3, ISSN:2405-4712, Pages:414-416

Mannan AA, Toya Y, Shimizu K, et al., 2015, Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism, Plos One, Vol:10, ISSN:1932-6203

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