Title
iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences.
Abstract
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.
Year
DOI
Venue
2018
10.1093/bioinformatics/bty140
BIOINFORMATICS
Field
DocType
Volume
Data mining,Dimensionality reduction,Computer science,Peptide,Data sequences,Cluster analysis,Python (programming language),Benchmarking,Encoding (memory),Web server
Journal
34
Issue
ISSN
Citations 
14
1367-4803
20
PageRank 
References 
Authors
0.67
9
11
Name
Order
Citations
PageRank
Zhen Chen1362.50
Pei Zhao2221.39
Fuyi Li39711.25
André Leier419719.87
Tatiana T. Marquez-Lago5779.01
Yanan Wang64411.61
Geoffrey I. Webb73130234.10
A. Ian Smith8322.88
Roger J. Daly9251.11
Kuo-Chen Chou1094664.26
Jiangning Song1137441.93