Intelligent Computing Theories and Application

occurringpolyphenols, responsible for alpha-synuclein amyloid disaggregation scheming towards effective therapeutics against Parkinson's disorder.- Study on the mechanism of Cistanche in the treatment of colorectal cancer based on network pharmacology.- A Novel Hybrid Machine Learning Approach Using Deep Learning for the Prediction of Alzheimer Disease Using Genome Data.- Prediction of Heart Disease Probability Based on Various Body Function.- Classification of Pulmonary Diseases from X-ray Images Using a Convolutional Neural Network.- Predicting lncRNA-disease associations based on tensor decomposition method.- AI in Skin Cancer Detection.- MiRNA-Disease Associations Prediction based on Neural Tensor Decomposition.- Gene Regulation Modeling and Analysis.- SHDC: A Method of Similarity Measurement Using Heat Kernel based on Denoising for Clustering scRNA-seq Data.- Research on RNA Secondary Structure Prediction Based on MLP.- Inference of Gene Regulatory Network from Time Series   Expression Data by Combining Local Geometric Similarity and Multivariate Regression.- Deep Convolution Recurrent Neural Network for Predicting RNA-Protein Binding Preference in mRNA UTR region.- Joint Association Analysis Method to Predict Genes Related to Liver Cancer.- A Hybrid Deep Neural Network for the Prediction of in-vivo Protein-DNA Binding by combining multiple-instance learning.- Using deep learning to predict transcription factor binding sites combining raw DNA sequence, evolutionary information and epigenomic data.- An abnormal gene detection method based on Selene.- A method for constructing an integrative network of competing endogenous RNAs.- Intelligent Computing in Computational Biology.- Detection of Drug-drug Interactions through Knowledge Graph Integrating Multi-attention with Capsule Network.- SCEC: A Novel Single-Cell Classification Method Based on Cell-Pair Ensemble Learning.- ICNNMDA: An Improved Convolutional Neural Network for Predicting miRNA-disease Associations.- DNA-GCN: Graph convolutional networks for predicting DNA-protein binding.- Weighted Nonnegative Matrix Factorization based on Multi-Source Fusion Information for Predicting CircRNA-Disease Associations.- ScSSC: semi-supervised single cell clustering based on 2D embedding.- SNEMO: Spectral Clustering Based on the Neighborhood for Multi-omics Data.- Covid-19 detection by Wavelet Entropy and Jaya.- An ensemble learning algorithm for predicting HIV-1 protease cleavage sites.- RWRNCP: Random Walking with Restart based Network Consistency Projection for Predicting miRNA-disease Association.- MELPMDA: A New Method Based on Matrix Enhancement and Label Propagation for Predicting miRNA-disease Association.- Prognostic prediction for non-small-cell lung cancer based on deep neural network and multimodal data.- Drug-Target Interactions Prediction with Feature Extraction Strategy Based on Graph Neural Network.- CNNEMS: Using Convolutional Neural Networks to Predict Drug-Target Interactions by Combining Protein Evolution and Molecular Structures Information.- A multi-graph deep learning model for predicting drug-disease associations.- Predicting Drug-disease Associations Based on Network Consistency Projection.- An efficient computational method to predict drug-target interactions utilizing matrix completion and linear optimization method.- Protein Structure and Function Prediction.- Protein-Protein Interaction Prediction by Integrating Sequence Information and Heterogeneous Network Representation.- DNA-Binding Protein Prediction Based on Deep Learning Feature Fusion.- Membrane Protein identification via multiple kernel fuzzy SVM.- Golgi Protein Prediction with Deep Forest.- Prediction of protein-protein interaction based on deep learning feature representation and random forest.-