期刊
BIOINFORMATICS
卷 34, 期 14, 页码 2499-2502出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/bty140
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资金
- Australian Research Council [ARC] [LP110200333, DP120104460]
- National Natural Science Foundation of China [NSFC] [31701142]
- National Health and Medical Research Council of Australia [NHMRC] [APP1058540]
- National Institute of Allergy and Infectious Diseases of the National Institutes of Health [R01 AI111965]
- Major Inter-Disciplinary Research (IDR) by Monash University
- Informatics startup packages through the UAB School of Medicine
Structural and physiochemical descriptors extracted from sequence data have been widely used to represent sequences and predict structural, functional, expression and interaction profiles of proteins and peptides as well as DNAs/RNAs. Here, we present iFeature, a versatile Python-based toolkit for generating various numerical feature representation schemes for both protein and peptide sequences. iFeature is capable of calculating and extracting a comprehensive spectrum of 18 major sequence encoding schemes that encompass 53 different types of feature descriptors. It also allows users to extract specific amino acid properties from the AAindex database. Furthermore, iFeature integrates 12 different types of commonly used feature clustering, selection and dimensionality reduction algorithms, greatly facilitating training, analysis and benchmarking of machine-learning models. The functionality of iFeature is made freely available via an online web server and a stand-alone toolkit.
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