Imperial College London

Professor Reiko J. Tanaka

Faculty of EngineeringDepartment of Bioengineering

Professor of Computational Systems Biology & Medicine



+44 (0)20 7594 6374r.tanaka Website




RSM 3.10Royal School of MinesSouth Kensington Campus





Professor Tanaka aims to search for fundamental rules and mechanisms of biological control and to make a decisive contribution to systems medicine and biology.

Mathematical modelling from the viewpoint of systems and control engineering allows us to investigate and extract common design principles in diverse systems across the cellular, tissue, organ and behavioural levels. Since most diseases are caused by malfunctioning of various regulatory mechanisms, understanding common control design principles helps to identify key mechanisms to investigate and propose and answer clinically/biologically relevant questions that could not even be posed without it.

For the details of her research interests, please see the Tanaka Group website.

Professor Tanaka has experience in multi-disciplinary research and education environments in research organisations in several countries. After she obtained her PhD from the Department of Mathematical Engineering and Information Physics, University of Tokyo, she was appointed as an Assistant Professor in the Department of Applied Physics and Physico-Informatics, Keio University. With her strong interest in the new area of systems biology, she obtained a fellowship from JSPS (Japan Society for the Promotion of Science) to join Professor John Doyle's group at the California Institute of Technology as a Visiting Associate. Since then she has been working in the area of systems biology from the systems and control viewpoint. Before joining Imperial, she was a research scientist in the Biological Control Systems lab. in RIKEN.

Reiko’s research publications can be found in the tab above, or on Google Scholar

Selected Publications

Journal Articles

Tanaka G, Dominguez-Huttinger E, Christodoulides P, et al., 2018, Bifurcation analysis of a mathematical model of atopic dermatitis to determine patient-specific effects of treatments on dynamic phenotypes, Journal of Theoretical Biology, Vol:448, ISSN:0022-5193, Pages:66-79

Domínguez-Hüttinger E, Christodoulides P, Miyauchi K, et al., 2017, Mathematical modeling of atopic dermatitis reveals "double switch" mechanisms underlying 4 common disease phenotypes, Journal of Allergy and Clinical Immunology, Vol:139, ISSN:0091-6749, Pages:1861-1872.e7

Dominguez-Huettinger E, Boon NJ, Clarke TB, et al., 2017, Mathematical Modeling of Streptococcus pneumoniae Colonization, Invasive Infection and Treatment, Frontiers in Physiology, Vol:8, ISSN:1664-042X

Lee SY, Boon NJ, Webb AAR, et al., 2016, Synergistic Activation of RD29A via Integration of Salinity Stress and Abscisic Acid in Arabidopsis thaliana, Plant and Cell Physiology, Vol:57, ISSN:1471-9053, Pages:2147-2160

Tanaka RJ, Boon NJ, Vrcelj K, et al., 2015, In silico modeling of spore inhalation reveals fungal persistence following low dose exposure, Scientific Reports, Vol:5, ISSN:2045-2322

Ono M, Tanaka RJ, 2015, Controversies concerning thymus-derived regulatory T cells: fundamental issues and a new perspective, Immunology and Cell Biology, Vol:94, ISSN:1440-1711, Pages:3-10

van Logtestijn MDA, Dominguez Huttinger E, Stamatas GN, et al., 2015, Resistance to Water Diffusion in the Stratum Corneum Is Depth-Dependent, PLOS One, Vol:10, ISSN:1932-6203

Tanaka RJ, Ono M, 2013, Skin Disease Modeling from a Mathematical Perspective, Journal of Investigative Dermatology, Vol:133, ISSN:0022-202X, Pages:1472-1478

Doyle JC, Alderson DL, Li L, et al., 2005, The "robust yet fragile" nature of the Internet, Proceedings of the National Academy of Sciences of the United States of America, Vol:102, ISSN:0027-8424, Pages:14497-14502

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