ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature
Published 2018 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature
Authors
Keywords
-
Journal
BMC BIOINFORMATICS
Volume 19, Issue 1, Pages -
Publisher
Springer Nature America, Inc
Online
2018-09-22
DOI
10.1186/s12859-018-2368-y
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- UniProt: the universal protein knowledgebase
- (2018) The UniProt Consortium NUCLEIC ACIDS RESEARCH
- EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation
- (2018) Afshine Amidi et al. PeerJ
- NewGOA: predicting new GO annotations of proteins by bi-random walks on a hybrid graph
- (2017) Guoxian Yu et al. IEEE-ACM Transactions on Computational Biology and Bioinformatics
- COFACTOR: improved protein function prediction by combining structure, sequence and protein–protein interaction information
- (2017) Chengxin Zhang et al. NUCLEIC ACIDS RESEARCH
- Large-scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants
- (2017) Ahmet Sureyya Rifaioglu et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- UniProt-DAAC: domain architecture alignment and classification, a new method for automatic functional annotation in UniProtKB
- (2016) Tunca Doğan et al. BIOINFORMATICS
- The Pfam protein families database: towards a more sustainable future
- (2015) Robert D. Finn et al. NUCLEIC ACIDS RESEARCH
- UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches
- (2014) B. E. Suzek et al. BIOINFORMATICS
- Accurate prediction of protein enzymatic class by N-to-1 Neural Networks
- (2013) Viola Volpato et al. BMC BIOINFORMATICS
- EFICAz2.5: application of a high-precision enzyme function predictor to 396 proteomes
- (2012) Narendra Kumar et al. BIOINFORMATICS
- ECOH: An Enzyme Commission number predictor using mutual information and a support vector machine
- (2012) Yoshihiko Matsuta et al. BIOINFORMATICS
- EnzML: multi-label prediction of enzyme classes using InterPro signatures
- (2012) Luna De Ferrari et al. BMC BIOINFORMATICS
- COFACTOR: an accurate comparative algorithm for structure-based protein function annotation
- (2012) Ambrish Roy et al. NUCLEIC ACIDS RESEARCH
- Prediction of Enzyme Subfamily Class via Pseudo Amino Acid Composition by Incorporating the Conjoint Triad Feature
- (2012) Yong-Cui Wang et al. PROTEIN AND PEPTIDE LETTERS
- LIBSVM
- (2012) Chih-Chung Chang et al. ACM Transactions on Intelligent Systems and Technology
- Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context
- (2011) Yong-Cui Wang et al. BMC Systems Biology
- Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference
- (2011) Nicolò Cesa-Bianchi et al. MACHINE LEARNING
- GOPred: GO Molecular Function Prediction by Combined Classifiers
- (2010) Ömer Sinan Saraç et al. PLoS One
- Efficiency analysis of KNN and minimum distance-based classifiers in enzyme family prediction
- (2009) Efendi Nasibov et al. COMPUTATIONAL BIOLOGY AND CHEMISTRY
- Subsequence-based feature map for protein function classification
- (2008) Omer Sinan Sarac et al. COMPUTATIONAL BIOLOGY AND CHEMISTRY
- Using support vector machines to distinguish enzymes: Approached by incorporating wavelet transform
- (2008) Jian-Ding Qiu et al. JOURNAL OF THEORETICAL BIOLOGY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search