This book constitutes the refereed proceedings of the 20th International Symposium on Bioinformatics Research and Applications, ISBRA 2024, held in Kunming, China, in July 19–21, 2024.The 93 full papers included in this book were carefully reviewed and selected from 236 submissions.

.- Exploring Hierarchical Structures of Cell Types in  scRNA-seq Data. .- Predicting Frequencies of Drug Side Effects Using Graph Attention Networks with Multiple Features. .- RabbitTrim: highly optimized trimming of Illumina sequencing data on multi-core platforms. .- A hybrid feature fusion network for predicting HER2 status on H&E-stained histopathology images. .- scCoRR: a data-driven self-correction framework for labeled scRNA-seq data. .- KT-AMP: Enhancing Antimicrobial Peptide Functions Prediction through Knowledge Transfer on Protein Language Model. .- A Multi-Scale Attention Network for Sleep Arousal Detection with Single-Channel ECG. .- RabbitSAlign: Accelerating Short-Read Alignment for CPU-GPU Heterogeneous Platforms. .- FedKD-DTI: Drug-Target Interaction Prediction Based on Federated Knowledge Distillation. .- Accurately Deciphering Novel Cell Type in Spatially Resolved Single-Cell Data through Optimal Transport. .- Synthesis of Boolean Networks with Weak and Strong Regulators. .- Patch-based coupled attention network to predict MSI status in colon cancer. .- Predicting Blood-Brain Barrier Permeability through Multi-View Graph Neural Network with Global-Attention and Pre-trained Transformer. .- LLMDTA: Improving Cold-Start Prediction in Drug-Target Affinity with Biological LLM. .- DMSDR: Drug Molecule Synergy-Enhanced Network for Drug Recommendation with Multi-Source Domain Knowledge. .- A Graph Transformer-Based Method for Predicting LncRNA-Disease Associations Using Matrix Factorization and Automatic Meta-Path Generation. .- The Dynamic Spatiotemporal Features Based on Rich Club Organization in Autism Spectrum Disorder. .- Integrated Analysis of Autophagy-Related Genes Identifies Diagnostic Biomarkers and Immune Correlates in Preeclampsia. .- Multi-Grained Cross-Modal Feature Fusion Network for Diagnosis Prediction. .- MOL-MOE：Learning Drug Molecular Characterization Based on Mixture of Expert Mechanism. .- A Multimodal Federated Learning Framework for Modality Incomplete Scenarios in Healthcare. .- FunBGC: An Intelligent Framework for Fungal Biosynthetic Gene Cluster Identification. .- An Automatic Recommendation Method  for Single-Cell DNA Variant Callers  Based on Meta-Learning Framework. .- Incomplete Multimodal Learning with Modality-Aware Feature Interaction for Brain Tumor Segmentation. .- Multi-Scale Mean Teacher for Unsupervised Cross-Modality Abdominal Segmentation with Limited Annotations. .- Subgraph-aware dynamic attention network for drug repositioning. .- Multi-filter based signed graph convolutional networks for predicting interactions on drug networks. .- CPSORCL: A Cooperative Particle Swarm Optimization Method with Random Contrastive Learning for Interactive Feature Selection. .- Hypergraph representation learning for cancer drug response prediction. .- DGCL: a contrastive learning method for predicting cancer driver genes based on graph diffusion. .- KUMA-MI: A 12-Lead Knowledge-guided Multi-branch Attention Networks for Myocardial Infarction Localization. .- scAHVC: Single-cell Multi-omics clustering algorithm based on adaptive weighted hyper-laplacian regularization. .- Early Prediction of SGA-LGA Fetus at the First Trimester Ending through Weighted Voting Ensemble Learning Approach. .- A Hierarchical Classification Model for Annotating Antibacterial Biocide and Metal Resistance Genes via Fusing Global and Local Semantics. .- Secure Relative Detection in (Forensic) Database with Homomorphic Encryption. Noninvasive diagnosis of cancer based on the heterogeneity and fragmentation features of cell-free mitochondrial DNA. .- A Novel Dual Interactive Network for Parkinson's Disease Diagnosis Based on Multi-modality Magnetic Resonance Imaging. .- DVMPDC: A deep learning model based on dual-view representation and multi-strategy pooling for predicting synergistic drug combinations. .- MEMDA: a multi-similarity integration pre-completion algorithm with error correction for predicting microbe-drug associations. .- ResDeepGS:A deep learning-based method for crop phenotype prediction. .- Benchmarking Biomedical Relation Knowledge in Large Language Models.

GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com