A Machine Learning Methodology for Enzyme Functional Classification Combining Structural and Protein Sequence Descriptors, Lecture Notes in Computer Science, vol.9656, pp.728-738, 2016. ,
DOI : 10.1007/978-3-319-31744-1_63
URL : https://hal.archives-ouvertes.fr/hal-01359157
-Nearest Neighbor Rule, Neural Computation, vol.12, issue.3, pp.731-740, 2005. ,
DOI : 10.1109/18.312167
Protein function prediction via graph kernels, Bioinformatics, vol.21, issue.Suppl 1, pp.47-56, 2005. ,
DOI : 10.1093/bioinformatics/bti1007
URL : https://academic.oup.com/bioinformatics/article-pdf/21/suppl_1/i47/524364/bti1007.pdf
Proteins, Journal of Proteome Research, vol.8, issue.9, pp.4372-4382, 1021. ,
DOI : 10.1021/pr9003163
3D entropy and moments prediction of enzyme classes and experimental-theoretic study of peptide fingerprints in Leishmania parasites, BBA)?Proteins and Proteomics 1794, pp.1784-1794, 2009. ,
DOI : 10.1016/j.bbapap.2009.08.020
Computational chemistry study of 3D-structure-function relationships for enzymes based on Markov models for protein electrostatic, HINT, and van der Waals potentials, Journal of Computational Chemistry, vol.67, issue.Database issue, pp.1510-1520, 2009. ,
DOI : 10.1002/jcc.21170
ENZPRED-Enzymatic Protein Class Predicting by Machine Learning, Current Topics in Medicinal Chemistry, vol.13, issue.14, pp.1674-1680, 2013. ,
DOI : 10.2174/15680266113139990118
Prediction of enzyme classification from protein sequence without the use of sequence similarity, Proceedings of the International Conference on Intelligent Systems for Molecular Biology, pp.92-99, 1997. ,
Practical limits of function prediction, 1<98::AID-PROT120>3.0.CO;2-S, pp.98-107, 2000. ,
DOI : 10.1002/1097-0134(20001001)41:1<98::AID-PROT120>3.0.CO;2-S
Predicting Enzyme Class From Protein Structure Without Alignments, Journal of Molecular Biology, vol.345, issue.1, pp.187-199, 2005. ,
DOI : 10.1016/j.jmb.2004.10.024
URL : http://cbio.ensmp.fr/~jvert/svn/bibli/local/Dobson2005Predicting.pdf
EnzML: multi-label prediction of enzyme classes using InterPro signatures, BMC Bioinformatics, vol.13, issue.1, pp.61-71, 2012. ,
DOI : 10.1093/bib/bbp047
Feature Extraction, Foundations and Applications, 2006. ,
A top-down approach to classify enzyme functional classes and sub-classes using random forest, EURASIP Journal on Bioinformatics and Systems Biology, vol.14, issue.Suppl 9, pp.1-10, 2012. ,
DOI : 10.1093/protein/14.9.615
Classification of Enzyme Function from Protein Sequence based on Feature Representation, 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering, pp.741-747, 2007. ,
DOI : 10.1109/BIBE.2007.4375643
3D representations of amino acids???applications to protein sequence comparison and classification, Computational and Structural Biotechnology Journal, vol.11, issue.18, pp.47-58, 2014. ,
DOI : 10.1016/j.csbj.2014.09.001
An extensive experimental comparison of methods for multi-label learning, Pattern Recognition, vol.45, issue.9, pp.3084-3104, 2012. ,
DOI : 10.1016/j.patcog.2012.03.004
Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism, BMC Genomics, vol.16, issue.Suppl 7, pp.16-26, 2015. ,
DOI : 10.1093/nar/gkl124
Enzymes/non-enzymes classification model complexity based on composition, sequence, 3D and topological indices, Journal of Theoretical Biology, vol.254, issue.2, pp.476-482, 2008. ,
DOI : 10.1016/j.jtbi.2008.06.003
A general method applicable to the search for similarities in the amino acid sequence of two proteins, Journal of Molecular Biology, vol.4870, issue.3, pp.443-453, 1970. ,
Hybrid learning algorithm in neural network system for enzyme classification, International Journal of Advances in Soft Computing and its Applications, vol.2, issue.2, pp.209-220, 2010. ,
Probabilistic outputs for support vector machines and comparison to regularized likelihood methods Advances in Large Margin Classifiers, pp.61-74, 1999. ,
EzyPred: A top???down approach for predicting enzyme functional classes and subclasses, Biochemical and Biophysical Research Communications, vol.364, issue.1, pp.53-59, 2007. ,
DOI : 10.1016/j.bbrc.2007.09.098
Identification of common molecular subsequences, Journal of Molecular Biology, vol.147, issue.1, pp.195-197, 1981. ,
DOI : 10.1016/0022-2836(81)90087-5
URL : http://www.cmb.usc.edu/papers/msw_papers/msw-042.pdf
Evolution of function in protein superfamilies, from a structural perspective 1 1Edited by A. R. Fersht, Journal of Molecular Biology, vol.307, issue.4, pp.1113-1143, 2001. ,
DOI : 10.1006/jmbi.2001.4513
Multi-Label Classification, International Journal of Data Warehousing and Mining, vol.3, issue.3, pp.1-13, 2007. ,
DOI : 10.4018/jdwm.2007070101
Automatic annotation of protein function, Current Opinion in Structural Biology, vol.15, issue.3, pp.267-274, 2005. ,
DOI : 10.1016/j.sbi.2005.05.010
Predicting enzymatic function from global binding site descriptors, Proteins: Structure, Function, and Bioinformatics, vol.95, issue.Suppl 6, pp.479-489, 2013. ,
DOI : 10.1073/pnas.95.26.15189
Accurate prediction of protein enzymatic class by N-to-1 Neural Networks, BMC Bioinformatics, vol.14, issue.Suppl 1, pp.11-21, 2013. ,
DOI : 10.1186/1472-6807-9-5
Classification of multi-family enzymes by multi-label machine learning and sequence-based descriptors, Analytical Methods, vol.307, issue.17, pp.6832-6840, 1039. ,
DOI : 10.1006/jmbi.2001.4513
Classification of Enzymes Using Machine Learning Based Approaches: A Review, Machine Learning and Applications: An International Journal, vol.2, issue.3/4, pp.30-49, 2015. ,
DOI : 10.5121/mlaij.2015.2404
Multilabel Neural Networks with Applications to Functional Genomics and Text Categorization, IEEE Transactions on Knowledge and Data Engineering, vol.18, issue.10, pp.1338-1351, 2006. ,
DOI : 10.1109/TKDE.2006.162
Classifying Multifunctional Enzymes by Incorporating Three Different Models into Chou???s General Pseudo Amino Acid Composition, The Journal of Membrane Biology, vol.10, issue.4, pp.551-557, 2016. ,
DOI : 10.2174/1570164611310010002
Identifying Multi-Functional Enzyme by Hierarchical Multi-Label Classifier, Journal of Computational and Theoretical Nanoscience, vol.10, issue.4, 2013. ,
DOI : 10.1166/jctn.2013.2804