Statistical analysis of modal gating in ion channels
- Submitting institution
-
Liverpool John Moores University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1404
- Type
- D - Journal article
- DOI
-
10.1098/rspa.2014.0030
- Title of journal
- PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
- Article number
- ARTN 20140030
- First page
- -
- Volume
- 470
- Issue
- 2166
- ISSN
- 1364-5021
- Open access status
- Out of scope for open access requirements
- Month of publication
- April
- Year of publication
- 2014
- 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
-
2
- Research group(s)
-
-
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work presents a statistically rigorous method for detecting changes of frequencies in long sequences. For sequences consisting of millions of data points, this is the only algorithm currently available that allows for calculating probability distributions of the changepoint locations. An analysis of activity changes in ion channels provided important insights into the biophysical processes underlying ion channel dynamics, leading to the development of a new modelling approach for ion channels. The first author was invited to the international workshop “Time Dynamic Change Point Models and its Applications” (https://www.uni-goettingen.de/en/workshop+time+dynamic+change+point+models+and+its+applications/495883.html, chair: Prof. Axel Munk, munk@math.uni-goettingen.de). An open-source software implementation is available.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
