Laboratory of Supramolecular Biology
Group of interdisciplinary Biology Laboratory (iBLab)

ProfessorShingo Iwami
Interdisciplinary life science
LecturerShoya Iwanami
Quantitative data analysis for cell differentiation
Laboratory HP
Shingo Iwami Professor
Lab members

Through the course of life, from the moment of birth till death, an organism will achieve various states of equilibrium or ‘homeostasis’ which will inevitably encounter perturbations. The processes of cell growth, differentiation, infection, mutation, evolution and adaptation work together as a coordinated ‘system’, described by mathematical models for population dynamics, to maintain a healthy state. Any disruptions to this system leads to disease including infection, allergy, cancer, and aging. We are conducting interdisciplinary research to elucidate “Quantitative Population Dynamics” through the course of life with original mathematical theory and computational simulation, which are both our CORE approach. Our mathematical model-based approach has quantitatively improved a current gold-standard approach essentially relying on the statistical analysis of “snapshot data” during dynamic interaction processes in life sciences research. Integrating current high-throughput technics including next-generation sequencer and mathematical sciences, we would like to make a paradigm shift in future life sciences research. Our developing approach could be applied to population dynamics of virus infections, immune system (e.g. differentiation process from hematopoietic stem cell or other specific immune cell) and to other aspects of cancer progression in terms of quantitative understandings for complex life phenomena including different time-scales and multi-layer data.


Using original mathematical theory and computational simulation as CORE approaches, we are actively involved in the discussion at early stage of interdisciplinary projects, such as identifying research questions and designing experiments and clinical trials, and lead them to success.


  1. KS Kim et al., "A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2", PLOS Biology, 19(3):e3001128. (2021)
  2. S. Iwanami et al., "Should a viral genome stay in the host cell or leave? A quantitative dynamics study of how hepatitis C virus deals with this dilemma", PLOS Biology, 18:e3000562 (2020).
  3. Y. Koizumi et al., "Quantifying antiviral activity optimizes drug combinations against hepatitis C virus infection", Proceedings of the National Academy of Sciences of the United States of America, 114: 1922-1927 (2017).
  4. S. Iwami et al., "Cell-to-cell infection by HIV contributes over half of virus infection", Elife, 4, (2015).