mlDEEPre: Multi-Functional Enzyme Function Prediction With Hierarchical Multi-Label Deep Learning
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- Type
- article
- Published
- 2019-01-22
- Cited by
- 106
- References
- 51
- Access
- Open access
- OpenAlex
- https://openalex.org/W2908663744
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:58535728
Keywords
Computer science, Flexibility (engineering), Function (biology), Artificial intelligence, Functional analysis
References
- DEEPre: sequence-based enzyme EC number prediction by deep learning
- EnzymeDetector: an integrated enzyme function prediction tool and database
- Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes.
- SVM-Prot: web-based support vector machine software for functional classification of a protein from its primary sequence
- The I-TASSER Suite: protein structure and function prediction
- The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000
- Human fatty acid synthase: structure and substrate selectivity of the thioesterase domain.
- Nature and Prevalence of Pain in Fabry Disease and Its Response to Enzyme Replacement Therapy—A Retrospective Analysis From the Fabry Outcome Survey
- EzyPred: a top-down approach for predicting enzyme functional classes and subclasses.
- Diverse and abundant antibiotic resistance genes in Chinese swine farms
- Current IUBMB recommendations on enzyme nomenclature and kinetics
- ML-KNN: A lazy learning approach to multi-label learning
- High frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells
- Predicting enzyme class from protein structure without alignments.
- iDNA-Prot: Identification of DNA Binding Proteins Using Random Forest with Grey Model
- COFACTOR: an accurate comparative algorithm for structure-based protein function annotation
- The Transporter Classification Database (TCDB): recent advances
- A new taxonomy-based protein fold recognition approach based on autocross-covariance transformation
- EFICAz: a comprehensive approach for accurate genome-scale enzyme function inference.
- EnzML: multi-label prediction of enzyme classes using InterPro signatures
Cited by
- DeepSimulator: a deep simulator for Nanopore sequencing
- PGCN: Disease gene prioritization by disease and gene embedding through graph convolutional neural networks
- Deep learning in bioinformatics: introduction, application, and perspective in big data era
- Using deep learning to annotate the protein universe
- Precise Prediction of Calpain Cleavage Sites and Their Aberrance Caused by Mutations in Cancer
- UDSMProt: universal deep sequence models for protein classification
- Machine learning techniques for protein function prediction
- Deep learning for mining protein data
- Exploration and Evaluation of Machine Learning-Based Models for Predicting Enzymatic Reactions
- MF-EFP: Predicting Multi-Functional Enzymes Function Using Improved Hybrid Multi-Label Classifier
- DeeReCT-APA: Prediction of Alternative Polyadenylation Site Usage Through Deep Learning
- DeTrac: Transfer Learning of Class Decomposed Medical Images in Convolutional Neural Networks
- The Classification of Enzymes by Deep Learning
- HECNet: a hierarchical approach to enzyme function classification using a Siamese Triplet Network
- Modern deep learning in bioinformatics
- In silico prediction of enzymatic reactions catalyzed by acid phosphatases
- Towards Structured Prediction in Bioinformatics with Deep Learning
- Predicting metabolic pathways of plant enzymes without using sequence similarity: Models from machine learning
- Image Recognition and Analysis of Intrauterine Residues Based on Deep Learning and Semi-Supervised Learning
- Coherent Hierarchical Multi-Label Classification Networks
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