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    <subfield code="a"> -- 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&amp;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&#xFF1A;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.</subfield>
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