Topological data analysis quantifies biological nano-structure from single molecule localization microscopy
- Submitting institution
-
The University of Birmingham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 91541655
- Type
- D - Journal article
- DOI
-
10.1093/bioinformatics/btz788
- Title of journal
- Bioinformatics
- Article number
- -
- First page
- 1614
- Volume
- 36
- Issue
- 5
- ISSN
- 1367-4803
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
7
- Research group(s)
-
-
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The organisation of molecular receptors on the surface of biological cells is known to be important in regulating cell function. We describe a new approach to understanding molecular organisation from single molecular microscopy data, drawing on ideas from computational topology to introduce a robust method for extracting and classifiying molecular clusters using a topological signature. To prevent spurious molecule detections from affecting the analysis, we introduce a novel bootstrap sampling procedure to measure the robustness of the signatures. The method was validated against known biological reference structures and is the first that can analyse individual clusters rather than ensemble averages.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -