ROSEFW-RF: the winner algorithm for the ECBDL’14 big data competition: an extremely imbalanced big data bioinformatics problem
- Submitting institution
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University of Nottingham, The
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1324169
- Type
- D - Journal article
- DOI
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10.1016/j.knosys.2015.05.027
- Title of journal
- Knowledge-Based Systems
- Article number
- -
- First page
- 69
- Volume
- 87
- Issue
- -
- ISSN
- 0950-7051
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2015
- 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
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5
- Research group(s)
-
-
- Citation count
- 64
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work presents a novel big data solution for a real-world biological problem that contributes to predicting the structure of a protein, a crucial step in understanding its function. From a computer science perspective, the challenge lies in the nature of the data, which is high dimensional, has a highly skewed class distribution, and massive volume. Previous approaches were not able to effectively exploit all available data to tackle this problem. This highly-cited solution won a Big Data Competition at the Genetic and Evolutionary Computation Conference.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
