Abstract
The Min protein system is arguably the best-studied model system for biological pattern formation. It exhibits pole-to-pole oscillations in E. coli bacteria as well as a variety of surface wave patterns in in vitro reconstitutions. Such Min surface wave patterns pose particular challenges to quantification as they are typically only semi-periodic and non-stationary. Here, we present a methodology for quantitatively analysing such Min patterns, aiming for reproducibility, user-independence, and easy usage. After introducing pattern-feature definitions and image-processing concepts, we present an analysis pipeline where we use autocorrelation analysis to extract global parameters such as the average spatial wavelength and oscillation period. Subsequently, we describe a method that uses flow-field analysis to extract local properties such as the wave propagation velocity. We provide descriptions on how to practically implement these quantification tools and provide Python code that can directly be used to perform analysis of Min patterns.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
