Closed-loop cycles of experiment design, execution, and learning accelerate systems biology model development in yeast
- Submitting institution
-
Goldsmiths' College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 3179
- Type
- D - Journal article
- DOI
-
10.1073/pnas.1900548116
- Title of journal
- Proceedings of the National Academy of Sciences
- Article number
- -
- First page
- 18142
- Volume
- 116
- Issue
- 36
- ISSN
- 0027-8424
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2019
- URL
-
http://research.gold.ac.uk/id/eprint/27135/
- 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
-
12
- Research group(s)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper reports on an AI system for automated improvement of complex Systems Biology computational models. The reported results are foundational for the development of a future generation of systems for automated scientific discovery. The paper presents the key results of the European project AdaLab (2014-2018) involving five Universities from three European countries, UK, France and Belgium (http://www.chistera.eu/projects/adalab). Soldatova was Coordinator of this successful project. The presented results formed a basis for the follow-up £1.4M EPSRC-funded project ACTION on cancer (2018-2022).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -