AIMC Journal:
IEEE transactions on computational biology and bioinformatics
Showing 21 to 30 of 56 articles
GMC-Bind: A Multimodal Framework for RNA-Protein Binding Site Prediction with Bidirectional Cross-Attentional Fusion.
IEEE transactions on computational biology and bioinformatics
Jun 3, 2026
Accurate identification of RNA-protein binding sites is crucial for understanding gene regulation and disease mechanisms. However, existing deep learning models still face challenges in synergistically modeling multi-scale sequence motifs and dynamic...
Hierarchical Molecular Attention Network: Improving Molecular Property Prediction Through Substructure Identification.
IEEE transactions on computational biology and bioinformatics
May 27, 2026
Few-shot molecular property prediction is a persisting challenge in many biology-related tasks, because the same molecule may exhibit different properties (e.g., active or inactive) in different tasks. Existing methods view all atoms as equally impor...
AdPrST:An Adversarial Graph Deep Learning Pre-clustering Framework for Deciphering Spatiotemporal Structures in Spatially Resolved Transcriptomics.
IEEE transactions on computational biology and bioinformatics
May 27, 2026
Spatially Resolved Transcriptomics (SRT) has revolutionized our understanding of gene expression within tissue microenvironments, yet accurately deciphering spatiotemporal structures-encompassing spatial domain identification, trajectory inference, a...
Minimum Description Length-Driven Fragment Mining for Pretraining Molecule Property Prediction Model.
IEEE transactions on computational biology and bioinformatics
May 26, 2026
Molecular fragments play a crucial role in molecular property prediction. However, most existing deep learning approaches rely heavily on expert-defined substructural patterns, limiting their ability to identify novel or latent fragments. This constr...
User-Guided Visual Analytics of Genome-wide DNA Methylation Data Based on Self-Organizing Maps.
IEEE transactions on computational biology and bioinformatics
May 25, 2026
DNA methylation is a key epigenetic modification with diagnostic and prognostic relevance across a wide range of diseases, particularly cancer. Modern array-based technologies enable high-throughput quantification of methylation states at hundreds of...
FGAIM: Identifying Drug-Target Activation and Inhibition Mechanisms via Inductive Graph Neural Networks Based on Fine-Grained Interaction Strategies.
IEEE transactions on computational biology and bioinformatics
May 21, 2026
Distinguishing the activation and inhibition mechanisms between drugs and targets can reveal the potential regulatory pathways of target functions, which is crucial in drug discovery and development. Although numerous deep learning based computationa...
Unveiling Viral Escape Mechanisms With Machine Learning: A Transformative Approach to Mutation Analysis for SARS-CoV-2 and Beyond.
IEEE transactions on computational biology and bioinformatics
May 20, 2026
Persistent viruses like Influenza, HIV, and Coronavirus exemplify the challenge of viral escape, significantly hindering the development of long-lasting vaccines and effective treatments. This study leverages a Long Short-Term Memory (LSTM) based dee...
Robust CRISPR-Cas Protein Identification using Max-Margin Regularized Transformer Models.
IEEE transactions on computational biology and bioinformatics
May 14, 2026
The discovery of CRISPR-Cas system has significantly advanced genome editing, offering vast applications in medical treatments and life sciences research. Despite their immense potential, the existing CRISPR-Cas systems still face challenges concerni...
Breast Cancer Biomarker Discovery Using an Enhanced Quantum-Based Avian Navigation Optimizer and Ensemble Learning Model.
IEEE transactions on computational biology and bioinformatics
May 11, 2026
Breast cancer remains a global health challenge, and early detection is crucial for improving survival rates. However, traditional biomarker detection methods in machine learning face challenges such as high false positives, large gene datasets, and ...
Deep Learning-based Volition Detection and Action Potential Extraction for Fully Automated Diagnosis of Neuromuscular Disease Using Needle Electromyography Signals.
IEEE transactions on computational biology and bioinformatics
May 8, 2026
OBJECTIVE: This study aimed to develop a deep learning-based volition-detection model to automate the diagnostic process and improve neuromuscular disease classification using needle electromyography (nEMG) signals. METHODS: The model was developed u...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32655
- Neural Networks, Computer 30545
- Algorithms 27797
- Deep Learning 27357
- Artificial Intelligence 25287
- Robotics 13443
- Image Processing, Computer-Assisted 9910
- Retrospective Studies 9561
- Magnetic Resonance Imaging 6493
- Reproducibility of Results 5753
- Tomography, X-Ray Computed 4970
- Support Vector Machine 4827
- Computational Biology 4407
- Brain 4196
- Computer Simulation 3970
Popular Journals
- ArXiv 42909
- Scientific reports 10182
- PloS one 5313
- bioRxiv 4918
- Sensors (Basel, Switzerland) 4795
- medRxiv 4068
- Neural networks : the official journal of the International Neural Network Society 3739
- Computers in biology and medicine 2046
- Computational intelligence and neuroscience 1932
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1569
- Nature communications 1405
- Journal of chemical information and modeling 1364
- IEEE journal of biomedical and health informatics 1343
- Journal of medical Internet research 1266