Yijie Ding

Publications

• Identification of Protein–Protein Interactions via a Novel Matrix-Based Sequence Representation Model with Amino Acid Contact Information
• DNA-binding protein prediction based on deep transfer learning
• Laplacian Regularized Sparse Representation Based Classifier for Identifying DNA N4-Methylcytosine Sites via L2,1/2-Matrix Norm
• A multi-layer multi-kernel neural network for determining associations between non-coding RNAs and diseases
• Prompt Learning for Multi-modal COVID-19 Diagnosis
• A review of methods for predicting DNA N6-methyladenine sites
• Prediction of Cell-Penetrating Peptides Using a Novel HSIC-Based Multiview TSK Fuzzy System
• Kernel Risk Sensitive Loss-based Echo State Networks for Predicting Therapeutic Peptides with Sparse Learning
• An Accurate Tool for Uncovering Cancer Subtypes by Fast Kernel Learning Method to Integrate Multiple Profile Data
• Random Fourier features-based sparse representation classifier for identifying DNA-binding proteins
• Impact of quarantine on fractional order dynamical model of Covid-19
• C-Loss Based Higher Order Fuzzy Inference Systems for Identifying DNA N4-Methylcytosine Sites
• Protein-DNA Binding Residues Prediction Using a Deep Learning Model with Hierarchical Feature Extraction
• iEnhancer-MRBF: Identifying enhancers and their strength with a multiple Laplacian-regularized radial basis function network
• A sequence-based multiple kernel model for identifying DNA-binding proteins
• A GHKNN model based on the physicochemical property extraction method to identify SNARE proteins
• RGCNCDA: Relational graph convolutional network improves circRNA-disease association prediction by incorporating microRNAs
• Subspace projection-based weighted echo state networks for predicting therapeutic peptides
• Identification of DNA-Binding Proteins via Hypergraph Based Laplacian Support Vector Machine
• FTWSVM-SR: DNA-Binding Proteins Identification via Fuzzy Twin Support Vector Machines on Self-Representation
• Identification of Vesicle Transport Proteins via Hypergraph Regularized K-Local Hyperplane Distance Nearest Neighbour Model
• Inferring human microbe–drug associations via multiple kernel fusion on graph neural network
• iPseU-TWSVM: Identification of RNA pseudouridine sites based on TWSVM
• ET-MSF: a model stacking framework to identify electron transport proteins
• Multivariate Information Fusion for Identifying Antifungal Peptides with Hilbert-Schmidt Independence Criterion
• A PLA2R-IgG4 Antibody-Based Predictive Model for Assessing Risk Stratification of Idiopathic Membranous Nephropathy
• G Protein-Coupled Receptor Interaction Prediction Based on Deep Transfer Learning
• MV-H-RKM: A Multiple View-based Hypergraph Regularized Restricted Kernel Machine for Predicting DNA-binding Proteins
• HKAM-MKM: A hybrid kernel alignment maximization-based multiple kernel model for identifying DNA-binding proteins
• Identification of DNA N4-methylcytosine sites via fuzzy model on self representation
• Identification of DNA N4-methylcytosine sites via multi-view kernel sparse representation model
• Sparse regularized joint projection model for identifying associations of non-coding RNAs and human diseases
• MLapSVM-LBS: Predicting DNA-binding proteins via a multiple Laplacian regularized support vector machine with local behavior similarity
• Identification of drug-target interactions via multiple kernel-based triple collaborative matrix factorization
• Application of DNA-Binding Protein Prediction Based on Graph Convolutional Network and Contact Map
• Immunoglobulin Classification Based on FC* and GC* Features
• A Reinforcement Learning-Based Model for Human MicroRNA-Disease Association Prediction
• Shared subspace-based radial basis function neural network for identifying ncRNAs subcellular localization
• Identify ncRNA Subcellular Localization via Graph Regularized κ-Local Hyperplane Distance Nearest Neighbor Model on Multi-Kernel Learning
• A Hybrid Model for Depression Detection With Transformer and Bi-directional Long Short-Term Memory
• Research on DNA-Binding Protein Identification Method Based on LSTM-CNN Feature Fusion
• Identification of drug-side effect association via restricted Boltzmann machines with penalized term
• Identification of protein-nucleotide binding residues via graph regularized k-local hyperplane distance nearest neighbor model
• An efficient multiple kernel support vector regression model for assessing dry weight of hemodialysis patients
• Identification of D Modification Sites Using a Random Forest Model Based on Nucleotide Chemical Properties
• Using a machine learning-based risk prediction model to analyze the coronary artery calcification score and predict coronary heart disease and risk assessment
• A Self-Representation-Based Fuzzy SVM Model for Predicting Vascular Calcification of Hemodialysis Patients
• Identification of DNA-binding proteins via Multi-view LSSVM with independence criterion
• Multi-View Kernel Sparse Representation for Identification of Membrane Protein Types
• Prediction of cell penetrating peptides and their uptake efficiency using random forest-based feature selections
• A deep multiple kernel learning-based higher-order fuzzy inference system for identifying DNA N4-methylcytosine sites
• Ranking near-native candidate protein structures via random forest classification
• A Novel Triple Matrix Factorization Method for Detecting Drug-Side Effect Association Based on Kernel Target Alignment
• Granular multiple kernel learning for identifying RNA-binding protein residues via integrating sequence and structure information
• Critical evaluation of web-based prediction tools for human protein subcellular localization
• Kernelized k-Local Hyperplane Distance Nearest-Neighbor Model for Predicting Cerebrovascular Disease in Patients With End-Stage Renal Disease
• Use Chou's 5-Step Rule to Predict DNA-Binding Proteins with Evolutionary Information
• Prediction of human protein subcellular localization using deep learning
• An two-layer predictive model of ensemble classifier chain for detecting antimicrobial peptides
• CEPZ: A Novel Predictor for Identification of DNase i Hypersensitive Sites
• Identification of drug-target interactions via multiple information integration
• Assessing Dry Weight of Hemodialysis Patients via Sparse Laplacian Regularized RVFL Neural Network with L2,1-Norm
• Identification of human microRNA-disease association via hypergraph embedded bipartite local model
• Identification of DNA-protein Binding Sites through Multi-Scale Local Average Blocks on Sequence Information
• Research on RNA secondary structure predicting via bidirectional recurrent neural network
• Membrane Protein Identification via Multiple Kernel Fuzzy SVM
• Membrane Protein Identification via Multi-view Graph Regularized k-Local Hyperplane Distance Nearest Neighbor Model
• An ameliorated prediction of drug–target interactions based on multi-scale discretewavelet transform and network features
• Identification of membrane protein types via multivariate information fusion with Hilbert–Schmidt Independence Criterion
• Identification of DNA-binding proteins by multiple kernel support vector machine and sequence information
• Identification of drug–target interactions via fuzzy bipartite local model
• Identification of Drug-Side Effect Association via Semisupervised Model and Multiple Kernel Learning
• Human protein subcellular localization identification via fuzzy model on Kernelized Neighborhood Representation
• Empirical Potential Energy Function Toward ab Initio Folding G Protein-Coupled Receptors
• Protein Crystallization Identification via Fuzzy Model on Linear Neighborhood Representation
• Improved detection of DNA-binding proteins via compression technology on PSSM information
• Identifying potential association on gene-disease network via dual hypergraph regularized least squares
• Identification of Drug–Target Interactions via Dual Laplacian Regularized Least Squares with Multiple Kernel Fusion
• Identification of drug-side effect association via multiple information integration with centered kernel alignment
• Identification of Protein-Ligand Binding Sites by Sequence Information and Ensemble Classifier
• Research on RNA Secondary Structure Prediction Based on Decision Tree
• A Prediction Method of DNA-Binding Proteins Based on Evolutionary Information
• Discovering cancer subtypes via an accurate fusion strategy on multiple profile data
• Research on RNA Secondary Structure Prediction Based on MLP
• Identification of DNA-Binding Proteins via Fuzzy Multiple Kernel Model and Sequence Information
• Multivariate information fusion with fast kernel learning to Kernel Ridge Regression in predicting lncRNA-protein interactions
• Identification of drug-target interactions via multi-view graph regularized link propagation model
• Exploring associations of non-coding RNAs in human diseases via three-matrix factorization with hypergraph-regular terms on center kernel alignment
• Mk-fsvm-svdd: A multiple kernel-based fuzzy svm model for predicting dna-binding proteins via support vector data description
• Identify RNA-associated subcellular localizations based on multi-label learning using Chou’s 5-steps rule
• Multiple Laplacian Regularized RBF Neural Network for Assessing Dry Weight of Patients With End-Stage Renal Disease
• MDA-SKF: Similarity Kernel Fusion for Accurately Discovering miRNA-Disease Association
• The computational models of drug-target interaction prediction
• Identifying ligand-receptor interactions via an integrated fuzzy model
• LPI-KTASLP: Prediction of LncRNA-Protein Interaction by Semi-Supervised Link Learning With Multivariate Information
• IEnhancer-KL: A Novel Two-Layer Predictor for Identifying Enhancers by Position Specific of Nucleotide Composition
• Assessing the Adequacy of Hemodialysis Patients via the Graph-Based Takagi-Sugeno-Kang Fuzzy System
• Drug–disease associations prediction via Multiple Kernel-based Dual Graph Regularized Least Squares
• FKRR-MVSF: A fuzzy kernel ridge regression model for identifying DNA-binding proteins by multi-view sequence features via chou’s five-step rule
• CrystalM: A Multi-View Fusion Approach for Protein Crystallization Prediction
• FKL-Spa-LapRLS: An accurate method for identifying human microRNA-disease association
• Identifying protein-protein interactions via many learning methods based on protein sequence information
• Protein–protein interface prediction based on hexagon structure similarity
• Knowledge flow modeling and analysis in supply chain based on stochastic Petri net
• Identification of Protein-Protein Interactions by Detecting Correlated Mutation at the Interface
• Predicting protein-protein interactions via multivariate mutual information of protein sequences
• Identification of residue-residue contacts using a novel coevolution- based method
• Multi-scale encoding of amino acid sequences for predicting protein interactions using gradient boosting decision tree
• Weighted Fuzzy System for Identifying DNA N4-Methylcytosine Sites With Kernel Entropy Component Analysis
• Low Rank Matrix Factorization Algorithm Based on Multi-Graph Regularization for Detecting Drug-Disease Association
• Multi-correntropy fusion based fuzzy system for predicting DNA N4-methylcytosine sites
• Multi-view local hyperplane nearest neighbor model based on independence criterion for identifying vesicular transport proteins