till Research summary

My main research interest is to understand principles of self-organisation in animal cell motion and cellular signalling. We use a combined approach based on quantitative image analysis and computational modelling to address problems ranging from the multicellular to the molecular level.
Examples of current projects are blebbing in Dictyostelium, cell movements during early chick development, and validation of mathematical models for cell orientation. Software we develop include our widely-used QuimP software for correlating cortical cell fluorescence with membrane movements, and LineageTracker, a multi feature cell tracker which allows to incorporate time-varying features to detect cell divisions. CellTracker is specifically dedicated to measuring periodic nuclear-cytoplasmic translocations of transcription factors. Current focus is on extending these methods to 3D and most recently we started to develop novel methods for GPU based real-time processing of light sheet microscopy data.

 

> Faculty page is here and includes links to software such as QuimP, CellTracker and Lineage Tracker

 

 

Bretschneider et al. (2016) Progress and perspectives in signal transduction, actin dynamics, and movement at the cell and tissue level: lessons from Dictyostelium.
Journal of the Royal Society Interface Focus, 6 20160047.

Bretschneider et al. (2016) Solving reaction-diffusion equations on evolving surfaces defined by biological image data.
arXiv:1606.05093.

Lockley et al. (2014) Image based validation of dynamical models for cell reorientation.
Cytometry A. 87:471-80.

Tyson et al. (2014) How blebs and pseudopods cooperate during chemotaxis.
Proc Natl Acad Sci U S A. 111(32):11703-8.