Machine learning and data mining frameworks for predicting drug response in cancer : An overview and a novel in silico screening process based on association rule mining
- Submitting institution
-
University of Dundee
- Unit of assessment
- 1 - Clinical Medicine
- Output identifier
- 48556926
- Type
- D - Journal article
- DOI
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10.1016/j.pharmthera.2019.107395
- Title of journal
- Pharmacology & Therapeutics
- Article number
- 107395
- First page
- -
- Volume
- 203
- Issue
- -
- ISSN
- 0163-7258
- Open access status
- Compliant
- Month of publication
- July
- 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
- No
- Number of additional authors
-
20
- Research group(s)
-
-
- Citation count
- 12
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- -
- Author contribution statement
- R Petty made a substantial contribution to the conception and design of the study; the organisation of the conduct of the study; carrying out the study; the analysis and interpretation of study data; and helping to draft the output and critiquing the output for important intellectual content.
- Non-English
- No
- English abstract
- -
