Bioinformatics Research and Applications

HCSeer: A Classification Tool for Human Genetic Variant Hot and Cold Spots Designed for PM1 and Benign Criteria in the ACMG Guideline.- ViDSG: A Hybrid Algorithm Integrating Statistical and Semantic Features via Dual-Channels for Identifying Prokaryotic and Eukaryotic Viruses.- MoGE: A Benchmark for Comprehensive Evaluation of Molecular Generation Models in De Novo Drug Design.- Dual-Modality Representation Learning for Molecular Property Prediction.- GDMRMD: An Ensemble Model for Predicting RNA Modification-Disease Associations.- SUIFS: A Symmetric Uncertainty based Interactive Feature Selection Method.- TF-GCNNovo: A Peptide Sequence Prediction Model Integrating Transformer and Graph Convolutional Network.- FSPicker: A Dual-Stream Attention Network for Multi-Scale Particle Picking in Cryo-Electron Tomography.- SDMFF: Spatial-temporal Dual-pathway Network with Multi-scale Feature Fusion for Parkinson's Disease Diagnosis.- RNA-ModCaller: A Multi Feature Fusion and Stacking Ensemble Learning Framework for Prediction of RNA Modifications.- Efficient and Accurate Approximation Algorithms for Protein Structure Alignment.- Multi-Task Learning with Cross-Stitch for Synergistic Effect of Drug Combination Prediction.- A Neighborhood Selection Learning Artificial Bee Colony Algorithm Based on Population Backtracking for Detecting Epistatic Interactions.- PDA-GTGCN: identification of piRNA-disease associations based on group feature transformation graph convolutional network.- DDLB: Using the protein language model and hierarchical architecture to improve disordered lipid-binding residues prediction.- EEG-TFNet: Spatiotemporal and Spectral Feature Integration for EEG-Based AD Detection.- RGMI: a multimodal graph framework with dynamic weighting for measuring disease similarity.- LDADW: An algorithm for integrating single-cell and spatial transcriptomic data based on the topic model.- Adaptive Fusion of Global and Local Representations for Neoantigen Retention Time Prediction through Hierarchical Sequence-Graph Hybridization.- MambaST: Hexagonal State Space Modeling for Spatial Domain Identification.- On Multiple Protein Scaffold Filling.- RGNCNDDA: Predicting Potential Drug-Disease Associations via Residual Graph Normalized Convolutional Network.- Spindle-UMamba: A Mamba-based Attention-Unet Framework for Effective Sleep Spindle Detection.- CADS: Causal Inference for Dissecting Essential Genes to Predict Drug Synergy.- A Novel Sample Selection for Deep Learning Model in Computational Drug Repositioning.- SGMDTI: A unified framework for drug-target interaction prediction by semantic-guided meta-path method.- TREPP: Tandem Repeat Expansion Pathogenicity Predicting Approach Using Stacked CatBoost Models and Multiple Features.- EMF: Enhancing Mortality Risk Prediction via Evidential Multimodal Fusion.- Contrastive Learning-based Method for Single-cell Multi-omics Data Clustering.- Intelligent algorithms of action recognition for cardiopulmonary resuscitation based on wearable device.- Label-guided graph contrastive learning for single-cell fusion clustering.- A Graph Convolution-Based Method for dental Image Registration.- DepMambaformer: Integrating Bidirectional State Space Duality Model with Multimodal Attention for Depression Detection.