iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences
Abstract Summary 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-ba...
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| Published in | Bioinformatics Vol. 34; no. 14; pp. 2499 - 2502 |
|---|---|
| Main Authors | , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Oxford University Press
15.07.2018
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1367-4803 1367-4811 1460-2059 1367-4811 |
| DOI | 10.1093/bioinformatics/bty140 |
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| Abstract | Abstract
Summary
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.
Availability and implementation
http://iFeature.erc.monash.edu/; https://github.com/Superzchen/iFeature/.
Supplementary information
Supplementary data are available at Bioinformatics online. |
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| AbstractList | 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.SummaryStructural 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.http://iFeature.erc.monash.edu/; https://github.com/Superzchen/iFeature/.Availability and implementationhttp://iFeature.erc.monash.edu/; https://github.com/Superzchen/iFeature/.Supplementary data are available at Bioinformatics online.Supplementary informationSupplementary data are available at Bioinformatics online. Abstract Summary 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. Availability and implementation http://iFeature.erc.monash.edu/; https://github.com/Superzchen/iFeature/. Supplementary information Supplementary data are available at Bioinformatics online. 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. http://iFeature.erc.monash.edu/; https://github.com/Superzchen/iFeature/. Supplementary data are available at Bioinformatics online. |
| Author | Chou, Kuo-Chen Li, Fuyi Wang, Yanan Webb, Geoffrey I Song, Jiangning Chen, Zhen Smith, A Ian Daly, Roger J Leier, André Marquez-Lago, Tatiana T Zhao, Pei |
| AuthorAffiliation | 8 Gordon Life Science Institute, Boston, MA, USA 9 Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China 1 School of Basic Medical Science, Qingdao University, 38 Dengzhou Road, Qingdao, China 3 Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC, Australia 5 Department of Cell, Developmental and Integrative Biology, School of Medicine, University of Alabama at Birmingham, AL, USA 2 State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, China 6 Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China 7 Monash Centre for Data Science, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia 4 Department of Genetics, School of Medicine, University of Alabama at Birmingham, AL, USA |
| AuthorAffiliation_xml | – name: 3 Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC, Australia – name: 5 Department of Cell, Developmental and Integrative Biology, School of Medicine, University of Alabama at Birmingham, AL, USA – name: 9 Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China – name: 1 School of Basic Medical Science, Qingdao University, 38 Dengzhou Road, Qingdao, China – name: 7 Monash Centre for Data Science, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia – name: 4 Department of Genetics, School of Medicine, University of Alabama at Birmingham, AL, USA – name: 6 Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China – name: 2 State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, China – name: 8 Gordon Life Science Institute, Boston, MA, USA |
| Author_xml | – sequence: 1 givenname: Zhen surname: Chen fullname: Chen, Zhen organization: School of Basic Medical Science, Qingdao University, 38 Dengzhou Road, Qingdao, China – sequence: 2 givenname: Pei surname: Zhao fullname: Zhao, Pei organization: State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences (CAAS), Anyang, China – sequence: 3 givenname: Fuyi surname: Li fullname: Li, Fuyi email: kcchou@gordonlifescience.org organization: Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC, Australia – sequence: 4 givenname: André surname: Leier fullname: Leier, André organization: Department of Genetics, School of Medicine, University of Alabama at Birmingham, AL, USA – sequence: 5 givenname: Tatiana T surname: Marquez-Lago fullname: Marquez-Lago, Tatiana T organization: Department of Genetics, School of Medicine, University of Alabama at Birmingham, AL, USA – sequence: 6 givenname: Yanan surname: Wang fullname: Wang, Yanan organization: Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, China – sequence: 7 givenname: Geoffrey I surname: Webb fullname: Webb, Geoffrey I organization: Monash Centre for Data Science, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia – sequence: 8 givenname: A Ian surname: Smith fullname: Smith, A Ian organization: Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC, Australia – sequence: 9 givenname: Roger J surname: Daly fullname: Daly, Roger J email: roger.daly@monash.edu organization: Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC, Australia – sequence: 10 givenname: Kuo-Chen surname: Chou fullname: Chou, Kuo-Chen email: kcchou@gordonlifescience.org organization: Gordon Life Science Institute, Boston, MA, USA – sequence: 11 givenname: Jiangning orcidid: 0000-0001-8031-9086 surname: Song fullname: Song, Jiangning email: jiangning.song@monash.edu organization: Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, VIC, Australia |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29528364$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1074/jbc.M401932200 10.1016/j.bbapap.2013.04.006 10.1093/bioinformatics/btv042 10.1038/nprot.2007.494 10.1186/1471-2105-9-310 10.1016/j.ab.2007.10.012 10.1093/nar/25.17.3389 10.1038/nrg3920 10.1006/bbrc.2000.3815 10.1093/nar/gkl305 10.1002/ajpa.20250 10.1093/bioinformatics/bth466 10.1016/j.bbrc.2004.06.073 10.1073/pnas.0607879104 10.1016/j.ab.2012.03.015 10.1093/bioinformatics/btq267 10.1093/bib/bbk007 10.1371/journal.pone.0017331 10.2174/1573406413666170515120507 10.1093/bioinformatics/btq043 10.1093/bioinformatics/btw564 10.1093/bioinformatics/btu624 10.1093/nar/gkr284 10.1016/j.jtbi.2010.12.024 10.1002/(SICI)1097-0134(19990601)35:4<401::AID-PROT3>3.0.CO;2-K 10.1371/journal.pcbi.1000636 10.1515/9781400874668 10.1089/omi.2015.0095 10.1073/pnas.92.19.8700 10.1093/bioinformatics/btt196 10.1016/S0006-3495(94)80782-9 10.1002/prot.1035 10.3390/ijms15033495 10.1093/bioinformatics/btt072 |
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| References | Cao (2023012713012398600_bty140-B5) 2013; 29 Bellman (2023012713012398600_bty140-B3) 1961 Chen (2023012713012398600_bty140-B8) 2013; 1834 Xiao (2023012713012398600_bty140-B35) 2015; 31 Chen (2023012713012398600_bty140-B7) 2013; 29 Du (2023012713012398600_bty140-B16) 2012; 425 Zuo (2023012713012398600_bty140-B36) 2017; 33 Chou (2023012713012398600_bty140-B9) 2000; 278 Li (2023012713012398600_bty140-B23) 2006; 34 Sokal (2023012713012398600_bty140-B32) 2006; 129 Song (2023012713012398600_bty140-B33) 2010; 26 Barkan (2023012713012398600_bty140-B2) 2010; 26 Chou (2023012713012398600_bty140-B11) 2005; 21 Schneider (2023012713012398600_bty140-B29) 1994; 66 Libbrecht (2023012713012398600_bty140-B24) 2015; 16 Shen (2023012713012398600_bty140-B30) 2007; 104 Lee (2023012713012398600_bty140-B22) 2011; 6 Shen (2023012713012398600_bty140-B31) 2008; 373 Chou (2023012713012398600_bty140-B15) 1978; 47 Dubchak (2023012713012398600_bty140-B19) 1999; 35 Altschul (2023012713012398600_bty140-B1) 1997; 25 Kawashima (2023012713012398600_bty140-B20) 2008; 36 (Database issue) Chou (2023012713012398600_bty140-B10) 2001; 43 Liu (2023012713012398600_bty140-B25) 2017; 13 Rottig (2023012713012398600_bty140-B27) 2010; 6 Larranaga (2023012713012398600_bty140-B21) 2006; 7 Tung (2023012713012398600_bty140-B34) 2008; 9 Du (2023012713012398600_bty140-B17) 2014; 15 Chou (2023012713012398600_bty140-B12) 2011; 273 Bhasin (2023012713012398600_bty140-B4) 2004; 279 Chou (2023012713012398600_bty140-B14) 2008; 3 Dubchak (2023012713012398600_bty140-B18) 1995; 92 Saravanan (2023012713012398600_bty140-B28) 2015; 19 Chou (2023012713012398600_bty140-B13) 2004; 320 Cao (2023012713012398600_bty140-B6) 2015; 31 Rao (2023012713012398600_bty140-B26) 2011; 39 |
| References_xml | – volume: 279 start-page: 23262 year: 2004 ident: 2023012713012398600_bty140-B4 article-title: Classification of nuclear receptors based on amino acid composition and dipeptide composition publication-title: J. Biol. Chem doi: 10.1074/jbc.M401932200 – volume: 1834 start-page: 1461 year: 2013 ident: 2023012713012398600_bty140-B8 article-title: hCKSAAP_UbSite: improved prediction of human ubiquitination sites by exploiting amino acid pattern and properties publication-title: Biochim. Biophys. Acta doi: 10.1016/j.bbapap.2013.04.006 – volume: 31 start-page: 1857 year: 2015 ident: 2023012713012398600_bty140-B35 article-title: protr/ProtrWeb: r package and web server for generating various numerical representation schemes of protein sequences publication-title: Bioinformatics doi: 10.1093/bioinformatics/btv042 – volume: 3 start-page: 153 year: 2008 ident: 2023012713012398600_bty140-B14 article-title: Cell-PLoc: a package of Web servers for predicting subcellular localization of proteins in various organisms publication-title: Nat. Protoc doi: 10.1038/nprot.2007.494 – volume: 9 start-page: 310 year: 2008 ident: 2023012713012398600_bty140-B34 article-title: Computational identification of ubiquitylation sites from protein sequences publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-9-310 – volume: 373 start-page: 386 year: 2008 ident: 2023012713012398600_bty140-B31 article-title: PseAAC: a flexible web server for generating various kinds of protein pseudo amino acid composition publication-title: Anal. Biochem doi: 10.1016/j.ab.2007.10.012 – volume: 25 start-page: 3389 year: 1997 ident: 2023012713012398600_bty140-B1 article-title: Gapped BLAST and PSI-BLAST: a new generation of protein database search programs publication-title: Nucleic Acids Res doi: 10.1093/nar/25.17.3389 – volume: 47 start-page: 45 year: 1978 ident: 2023012713012398600_bty140-B15 article-title: Prediction of the secondary structure of proteins from their amino acid sequence publication-title: Adv. Enzymol. Relat. Areas Mol. Biol – volume: 16 start-page: 321 year: 2015 ident: 2023012713012398600_bty140-B24 article-title: Machine learning applications in genetics and genomics publication-title: Nat. Rev. Genet doi: 10.1038/nrg3920 – volume: 278 start-page: 477 year: 2000 ident: 2023012713012398600_bty140-B9 article-title: Prediction of protein subcellular locations by incorporating quasi-sequence-order effect publication-title: Biochem. Biophys. Res. Commun doi: 10.1006/bbrc.2000.3815 – volume: 34 start-page: W32 year: 2006 ident: 2023012713012398600_bty140-B23 article-title: PROFEAT: a web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence publication-title: Nucleic Acids Res doi: 10.1093/nar/gkl305 – volume: 129 start-page: 121 year: 2006 ident: 2023012713012398600_bty140-B32 article-title: Population structure inferred by local spatial autocorrelation: an example from an Amerindian tribal population publication-title: Am. J. Phys. Anthropol doi: 10.1002/ajpa.20250 – volume: 21 start-page: 10 year: 2005 ident: 2023012713012398600_bty140-B11 article-title: Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes publication-title: Bioinformatics doi: 10.1093/bioinformatics/bth466 – volume: 320 start-page: 1236 year: 2004 ident: 2023012713012398600_bty140-B13 article-title: Prediction of protein subcellular locations by GO-FunD-PseAA predictor publication-title: Biochem. Biophys. Res. Commun doi: 10.1016/j.bbrc.2004.06.073 – volume: 104 start-page: 4337 year: 2007 ident: 2023012713012398600_bty140-B30 article-title: Predicting protein-protein interactions based only on sequences information publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.0607879104 – volume: 425 start-page: 117 year: 2012 ident: 2023012713012398600_bty140-B16 article-title: PseAAC-Builder: a cross-platform stand-alone program for generating various special Chou’s pseudo-amino acid compositions publication-title: Anal. Biochem doi: 10.1016/j.ab.2012.03.015 – volume: 26 start-page: 1714 year: 2010 ident: 2023012713012398600_bty140-B2 article-title: Prediction of protease substrates using sequence and structure features publication-title: Bioinformatics doi: 10.1093/bioinformatics/btq267 – volume: 7 start-page: 86 year: 2006 ident: 2023012713012398600_bty140-B21 article-title: Machine learning in bioinformatics publication-title: Brief. Bioinform doi: 10.1093/bib/bbk007 – volume: 36 (Database issue) start-page: D202 year: 2008 ident: 2023012713012398600_bty140-B20 article-title: AAindex: amino acid index database, progress report 2008 publication-title: Nucleic Acids Res – volume: 6 start-page: e17331 year: 2011 ident: 2023012713012398600_bty140-B22 article-title: Incorporating distant sequence features and radial basis function networks to identify ubiquitin conjugation sites publication-title: PLoS One doi: 10.1371/journal.pone.0017331 – volume: 13 start-page: 552 year: 2017 ident: 2023012713012398600_bty140-B25 article-title: iPGK-PseAAC: identify lysine phosphoglycerylation sites in proteins by incorporating four different tiers of amino acid pairwise coupling information into the general PseAAC publication-title: Med. Chem doi: 10.2174/1573406413666170515120507 – volume: 26 start-page: 752 year: 2010 ident: 2023012713012398600_bty140-B33 article-title: Cascleave: towards more accurate prediction of caspase substrate cleavage sites publication-title: Bioinformatics doi: 10.1093/bioinformatics/btq043 – volume: 33 start-page: 122 year: 2017 ident: 2023012713012398600_bty140-B36 article-title: PseKRAAC: a flexible web server for generating pseudo K-tuple reduced amino acids composition publication-title: Bioinformatics doi: 10.1093/bioinformatics/btw564 – volume: 31 start-page: 279 year: 2015 ident: 2023012713012398600_bty140-B6 article-title: Rcpi: r /Bioconductor package to generate various descriptors of proteins, compounds and their interactions publication-title: Bioinformatics doi: 10.1093/bioinformatics/btu624 – volume: 39 start-page: W385 year: 2011 ident: 2023012713012398600_bty140-B26 article-title: Update of PROFEAT: a web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence publication-title: Nucleic Acids Res doi: 10.1093/nar/gkr284 – volume: 273 start-page: 236 year: 2011 ident: 2023012713012398600_bty140-B12 article-title: Some remarks on protein attribute prediction and pseudo amino acid composition publication-title: J. Theor. Biol doi: 10.1016/j.jtbi.2010.12.024 – volume: 35 start-page: 401 year: 1999 ident: 2023012713012398600_bty140-B19 article-title: Recognition of a protein fold in the context of the Structural Classification of Proteins (SCOP) classification publication-title: Proteins doi: 10.1002/(SICI)1097-0134(19990601)35:4<401::AID-PROT3>3.0.CO;2-K – volume: 6 start-page: e1000636 year: 2010 ident: 2023012713012398600_bty140-B27 article-title: Combining structure and sequence information allows automated prediction of substrate specificities within enzyme families publication-title: PLoS Comput. Biol doi: 10.1371/journal.pcbi.1000636 – volume-title: Adaptive Control Processes: A Guided Tour year: 1961 ident: 2023012713012398600_bty140-B3 doi: 10.1515/9781400874668 – volume: 19 start-page: 648 year: 2015 ident: 2023012713012398600_bty140-B28 article-title: Harnessing computational biology for exact linear B-cell epitope prediction: a novel amino acid composition-based feature descriptor publication-title: Omics doi: 10.1089/omi.2015.0095 – volume: 92 start-page: 8700 year: 1995 ident: 2023012713012398600_bty140-B18 article-title: Prediction of protein folding class using global description of amino acid sequence publication-title: Proc. Natl. Acad. Sci. USA doi: 10.1073/pnas.92.19.8700 – volume: 29 start-page: 1614 year: 2013 ident: 2023012713012398600_bty140-B7 article-title: Incorporating key position and amino acid residue features to identify general and species-specific Ubiquitin conjugation sites publication-title: Bioinformatics doi: 10.1093/bioinformatics/btt196 – volume: 66 start-page: 335 year: 1994 ident: 2023012713012398600_bty140-B29 article-title: The rational design of amino acid sequences by artificial neural networks and simulated molecular evolution: de novo design of an idealized leader peptidase cleavage site publication-title: Biophys. J doi: 10.1016/S0006-3495(94)80782-9 – volume: 43 start-page: 246 year: 2001 ident: 2023012713012398600_bty140-B10 article-title: Prediction of protein cellular attributes using pseudo-amino acid composition publication-title: Proteins doi: 10.1002/prot.1035 – volume: 15 start-page: 3495 year: 2014 ident: 2023012713012398600_bty140-B17 article-title: PseAAC-General: fast building various modes of general form of Chou’s pseudo-amino acid composition for large-scale protein datasets publication-title: Int. J. Mol. Sci doi: 10.3390/ijms15033495 – volume: 29 start-page: 960 year: 2013 ident: 2023012713012398600_bty140-B5 article-title: propy: a tool to generate various modes of Chou’s PseAAC publication-title: Bioinformatics doi: 10.1093/bioinformatics/btt072 |
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Structural and physiochemical descriptors extracted from sequence data have been widely used to represent sequences and predict structural,... Structural and physiochemical descriptors extracted from sequence data have been widely used to represent sequences and predict structural, functional,... |
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| SubjectTerms | Applications Notes Machine Learning Molecular Sequence Annotation Peptides - chemistry Peptides - metabolism Peptides - physiology Protein Conformation Proteins - chemistry Proteins - metabolism Proteins - physiology Sequence Analysis, Protein - methods Software |
| Title | iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences |
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