AIMC Topic: Computational Biology

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GRATCR: Epitope-Specific T Cell Receptor Sequence Generation With Data-Efficient Pre-Trained Models.

IEEE journal of biomedical and health informatics Mar 6, 2025
T cell receptors (TCRs) play a crucial role in numerous immunotherapies targeting tumor cells. However, their acquisition and optimization present significant challenges, involving laborious and time-consuming wet lab experimental resource. Deep gene...
Computational Biology Humans Sequence Analysis, Protein Deep Learning Receptors, Antigen, T-Cell Epitopes, T-Lymphocyte
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CardiOT: Towards Interpretable Drug Cardiotoxicity Prediction Using Optimal Transport and Kolmogorov--Arnold Networks.

IEEE journal of biomedical and health informatics Mar 6, 2025
Investigating the inhibitory effects of compounds on cardiac ion channels is essential for assessing cardiac drug safety. Consequently, researchers have developed computational models to evaluate combined cardiotoxicity (CCT) on cardiac ion channels....
Humans Computational Biology Neural Networks, Computer Cardiotoxicity Models, Cardiovascular Ion Channels
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NPENN: A Noise Perturbation Ensemble Neural Network for Microbiome Disease Phenotype Prediction.

IEEE journal of biomedical and health informatics Mar 6, 2025
With advances in microbiomics, the crucial role of microbes in disease progression is increasingly recognized. However, predicting disease phenotypes using microbiome data remains challenging due to data complexity, heterogeneity, and limited model g...
Microbiota Phenotype Humans Computational Biology Neural Networks, Computer
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Drug Repositioning via Multi-View Representation Learning With Heterogeneous Graph Neural Network.

IEEE journal of biomedical and health informatics Mar 6, 2025
Exploring simple and efficient computational methods for drug repositioning has emerged as a popular and compelling topic in the realm of comprehensive drug development. The crux of this technology lies in identifying potential drug-disease associati...
Computational Biology Drug Repositioning Graph Neural Networks Neural Networks, Computer Algorithms Humans
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Knowledge Graph Neural Network With Spatial-Aware Capsule for Drug-Drug Interaction Prediction.

IEEE journal of biomedical and health informatics Mar 6, 2025
Uncovering novel drug-drug interactions (DDIs) plays a pivotal role in advancing drug development and improving clinical treatment. The outstanding effectiveness of graph neural networks (GNNs) has garnered significant interest in the field of DDI pr...
Graph Neural Networks Computational Biology Drug Interactions Neural Networks, Computer Algorithms Humans
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Multimodal Drug Target Binding Affinity Prediction Using Graph Local Substructure.

IEEE journal of biomedical and health informatics Mar 6, 2025
Predicting the binding affinity of drug target is essential to reduce drug development costs and cycles. Recently, several deep learning-based methods have been proposed to utilize the structural or sequential information of drugs and targets to pred...
Pharmaceutical Preparations Computational Biology Proteins Deep Learning Protein Binding Humans Algorithms Drug Discovery
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BINDTI: A Bi-Directional Intention Network for Drug-Target Interaction Identification Based on Attention Mechanisms.

IEEE journal of biomedical and health informatics Mar 6, 2025
The identification of drug-target interactions (DTIs) is an essential step in drug discovery. In vitro experimental methods are expensive, laborious, and time-consuming. Deep learning has witnessed promising progress in DTI prediction. However, how t...
Proteins Deep Learning Computational Biology Humans Neural Networks, Computer Drug Discovery
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DRGCL: Drug Repositioning via Semantic-Enriched Graph Contrastive Learning.

IEEE journal of biomedical and health informatics Mar 6, 2025
Drug repositioning greatly reduces drug development costs and time by discovering new indications for existing drugs. With the development of technology and large-scale biological databases, computational drug repositioning has increasingly attracted...
Humans Algorithms Databases, Factual Neural Networks, Computer Machine Learning Semantics Computational Biology Drug Repositioning
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Dual Representation Learning for Predicting Drug-Side Effect Frequency Using Protein Target Information.

IEEE journal of biomedical and health informatics Mar 6, 2025
Knowledge of unintended effects of drugs is critical in assessing the risk of treatment and in drug repurposing. Although numerous existing studies predict drug-side effect presence, only four of them predict the frequency of the side effects. Unfort...
Proteins Humans Deep Learning Drug-Related Side Effects and Adverse Reactions Computational Biology
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Prediction of Drug-Target Interactions With High- Quality Negative Samples and a Network-Based Deep Learning Framework.

IEEE journal of biomedical and health informatics Mar 6, 2025
Identification of drug-target interactions (DTIs) plays a crucial role in drug discovery. Compared to traditional experimental methods, computer-based methods for predicting DTIs can significantly reduce the time and financial burdens of drug develop...
Drug Discovery Deep Learning Humans Neural Networks, Computer Pharmaceutical Preparations Computational Biology Gene Ontology Proteins
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