ArticleProtein science : a publication of the Protein Society2004
Predicting enzyme family class in a hybridization space.
Article in Protein science : a publication of the Protein Society, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- A general model for predicting enzyme functions based on enzymatic reactions.Journal of cheminformatics · 2024Article
- PredictEFC: a fast and efficient multi-label classifier for predicting enzyme family classes.BMC bioinformatics · 2024Article
- Using several pseudo amino acid composition types and different machine learning algorithms to classify and predict archaeal phospholipases.Molecular biology research communications · 2023Article
- IHEC_RAAC: a online platform for identifying human enzyme classes via reduced amino acid cluster strategy.Amino acids · 2021Article
- iATC-mHyb: a hybrid multi-label classifier for predicting the classification of anatomical therapeutic chemicals.Oncotarget · 2017Article
- A Treatise to Computational Approaches Towards Prediction of Membrane Protein and Its Subtypes.The Journal of membrane biology · 2017Review
- Classifying Multifunctional Enzymes by Incorporating Three Different Models into Chou's General Pseudo Amino Acid Composition.The Journal of membrane biology · 2016Article
- A Prediction Model for Membrane Proteins Using Moments Based Features.BioMed research international · 2016Article
- Application of improved three-dimensional kernel approach to prediction of protein structural class.BioMed research international · 2013Article
- Computational Approaches for Automated Classification of Enzyme Sequences.Journal of proteomics & bioinformatics · 2011Article
- Prediction of antimicrobial peptides based on sequence alignment and feature selection methods.PloS one · 2011Article
- Some remarks on protein attribute prediction and pseudo amino acid composition.Journal of theoretical biology · 2011Article
- Molecular biocoding of insulin.Advances and applications in bioinformatics and chemistry : AABC · 2010Article
- Efficacy of different protein descriptors in predicting protein functional families.BMC bioinformatics · 2007Article
- Prediction of protein submitochondria locations by hybridizing pseudo-amino acid composition with various physicochemical features of segmented sequence.BMC bioinformatics · 2006Article
- Prediction of protein structural class with Rough Sets.BMC bioinformatics · 2006Article
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2 authors.
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Abstract
Given the sequence of a protein, how can we predict whether it is an enzyme or a non-enzyme? If it is, what enzyme family class it belongs to? Because these questions are closely relevant to the biological function of a protein and its acting object, their importance is self-evident. Particularly with the explosion of protein sequences entering into data banks and the relatively much slower progress in using biochemical experiments to determine their functions, it is highly desired to develop an automated method that can be used to give fast answers to these questions. By hybridizing the gene ontology and pseudo-amino-acid composition, we have introduced a new method that is called GO-PseAA predictor and operate it in a hybridization space. To avoid redundancy and bias, demonstrations were performed on a data set in which none of the proteins in an individual class has > or =40% sequence identity to any other. The overall success rate thus obtained by the jackknife cross-validation test in identifying enzyme and non-enzyme was 93%, and that in identifying the enzyme family was 94% for the following six main Enzyme Commission (EC) classes: (1) oxidoreductase, (2) transferase, (3) hydrolase, (4) lyase, (5) isomerase, and (6) ligase. The corresponding rates by the independent data set test were 98% and 97%, respectively.
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