Automatic selection of verification tools for efficient analysis of biochemical models
- Submitting institution
-
The University of Sheffield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2458
- Type
- D - Journal article
- DOI
-
10.1093/bioinformatics/bty282
- Title of journal
- Bioinformatics
- Article number
- -
- First page
- 3187
- Volume
- 34
- Issue
- 18
- ISSN
- 1367-4803
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2018
- 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
- No
- Number of additional authors
-
4
- Research group(s)
-
I - Verification
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Verification of biochemical models is crucial to modern biological research, but existing tools use different formats and protocols, and identifying the best one requires computational expertise that is unavailable in most labs. Running all tools in parallel is unsustainable, since this uses power unnecessarily. The work reported here solves this important problem for the first time by automatically identifying and running the best verifier.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -