This two-set volume LNCS 15756 and 15767 constitutes the refereed proceedings of the 21st International Symposium on Bioinformatics Research and Applications, ISBRA 2025, held in Helsinki, Finland, during August 35, 2025.

The 66 full papers were carefully reviewed and selected from 167 submissions. This year's symposium brought together leading researchers, scientists, and industry professionals from around the world to share cutting-edge advancements, foster collaboration, and explore the future of bioinformatics and computational biology.

Inhalt

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.