Quantitative prediction of peptide binding affinity by using hybrid fuzzy support vector regression
- Submitting institution
-
Staffordshire University
- Unit of assessment
- 3 - Allied Health Professions, Dentistry, Nursing and Pharmacy
- Output identifier
- 6742
- Type
- D - Journal article
- DOI
-
10.1016/j.asoc.2016.01.024
- Title of journal
- Applied Soft Computing
- Article number
- -
- First page
- 210
- Volume
- 43
- Issue
- -
- ISSN
- 1568-4946
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2016
- URL
-
https://www.sciencedirect.com/science/article/pii/S1568494616300114?via%3Dihub
- 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
-
1
- Research group(s)
-
A - Biosciences Research Hub (BRH)
- Citation count
- 18
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- -
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
