Cell Fates, Cell States, and Cell Maps


All of the 70 trillion or so cells in an adult human stem from a single progenitor: a fertilised egg cell. We want to understand the processes that drive this development. To be able to achieve this cells must be able to sense and respond to their environment, and all the cells in a multi-cellular organism must dynamically self-organise. We want to understand how cells process information and “make decisions.”

Mathematical models, including comprehensive models of whole cells — CellMaps — are our tool of choice to study these phenomena. Constructing these CellMaps, analysing their behaviour, and mapping out strategies through which we can control their behaviour are core aims of our research. This requires the development of new mathematics and new computational tools. We are working on CellMaps across the whole tree of life: from bacteria to complex multicellular organisms.

Ultimately these models — CellMaps and whole cell models — will allow us to test our understanding of biology, make predictions, and learn how to control and guide cellular behaviour in synthetic biology and precision healthcare.

Crucially, this theme also shows that we are fans of the Oxford comma.

Latest research

2018

Tomasz Jetka; Karol Nienałtowski; Sarah Filippi; Michael P.H. Stumpf; Michał Komorowski

An information-theoretic framework for deciphering pleiotropic and noisy biochemical signaling Journal Article

In: Nat Commun, vol. 9, no. 1, 2018, ISSN: 2041-1723.

Abstract | Links | BibTeX | Tags: Fate cells | Cell states and Cell maps, Stochastic and nonlinear biological dynamics

2017

Adam L. MacLean; Maia A. Smith; Juliane Liepe; Aaron Sim; Reema Khorshed; Narges M. Rashidi; Nico Scherf; Axel Krinner; Ingo Roeder; Cristina Lo Celso; Michael P.H. Stumpf

Single Cell Phenotyping Reveals Heterogeneity Among Hematopoietic Stem Cells Following Infection Journal Article

In: vol. 35, no. 11, pp. 2292–2304, 2017, ISSN: 1549-4918.

Abstract | Links | BibTeX | Tags: Fate cells | Cell states and Cell maps, Stochastic and nonlinear biological dynamics

2016

Helen Weavers; Juliane Liepe; Aaron Sim; Will Wood; Paul Martin; Michael P.H. Stumpf

Systems Analysis of the Dynamic Inflammatory Response to Tissue Damage Reveals Spatiotemporal Properties of the Wound Attractant Gradient Journal Article

In: Current Biology, vol. 26, no. 15, pp. 1975–1989, 2016, ISSN: 0960-9822.

Links | BibTeX | Tags: Fate cells | Cell states and Cell maps, Stochastic and nonlinear biological dynamics

Sarah Filippi; Chris P. Barnes; Paul D.W. Kirk; Takamasa Kudo; Katsuyuki Kunida; Siobhan S. McMahon; Takaho Tsuchiya; Takumi Wada; Shinya Kuroda; Michael P.H. Stumpf

Robustness of MEK-ERK Dynamics and Origins of Cell-to-Cell Variability in MAPK Signaling Journal Article

In: Cell Reports, vol. 15, no. 11, pp. 2524–2535, 2016, ISSN: 2211-1247.

Links | BibTeX | Tags: Fate cells | Cell states and Cell maps, Stochastic and nonlinear biological dynamics