AIMC Topic: Computational Biology

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Contrasting Multi-Source Temporal Knowledge Graphs for Biomedical Hypothesis Generation.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Hypothesis Generation (HG) aims to expedite biomedical researches by generating novel hypotheses from existing scientific literature. Most existing studies focused on modeling static snapshots of the corpus, neglecting the temporal evolution of scien...
Biomedical Research Computational Biology Knowledge Bases Data Mining Algorithms Humans Databases, Factual Machine Learning
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KGRACDA: A Model Based on Knowledge Graph from Recursion and Attention Aggregation for CircRNA-Disease Association Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
CircRNA is closely related to human disease, so it is important to predict circRNA-disease association (CDA). However, the traditional biological detection methods have high difficulty and low accuracy, and computational methods represented by deep l...
Computational Biology Datasets as Topic Databases, Genetic Models, Genetic RNA, Circular Knowledge Bases Humans Genetic Predisposition to Disease
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Parallel Convolutional Contrastive Learning Method for Enzyme Function Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
The function labeling of enzymes has a wide range of application value in the medical field, industrial biology and other fields. Scientists define enzyme categories by enzyme commission (EC) numbers. At present, although there are some tools for enz...
Databases, Protein Enzymes Deep Learning Computational Biology Machine Learning Neural Networks, Computer Algorithms
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Integrating K+ Entities Into Coreference Resolution on Biomedical Texts.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Biomedical Coreference Resolution focuses on identifying the coreferences in biomedical texts, which normally consists of two parts: (i) mention detection to identify textual representation of biological entities and (ii) finding their coreference li...
Humans Neural Networks, Computer Natural Language Processing Data Mining Deep Learning Algorithms Computational Biology Databases, Factual
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Deep Learning in Gene Regulatory Network Inference: A Survey.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Understanding the intricate regulatory relationships among genes is crucial for comprehending the development, differentiation, and cellular response in living systems. Consequently, inferring gene regulatory networks (GRNs) based on observed data ha...
Computational Biology Deep Learning Gene Regulatory Networks Humans
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Joint Extraction of Biomedical Events Based on Dynamic Path Planning Strategy and Hybrid Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Biomedical event detection is a pivotal information extraction task in molecular biology and biomedical research, which provides inspiration for the medical search, disease prevention, and new drug development. The existing methods usually detect sim...
Databases, Factual Biomedical Research Computational Biology Data Mining Neural Networks, Computer Algorithms Humans
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AGML: Adaptive Graph-Based Multi-Label Learning for Prediction of RBP and as Event Associations During EMT.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Increasing evidence has indicated that RNA-binding proteins (RBPs) play an essential role in mediating alternative splicing (AS) events during epithelial-mesenchymal transition (EMT). However, due to the substantial cost and complexity of biological ...
Algorithms Computational Biology Humans Machine Learning Alternative Splicing RNA-Binding Proteins Epithelial-Mesenchymal Transition
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DMAMP: A Deep-Learning Model for Detecting Antimicrobial Peptides and Their Multi-Activities.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Due to the broad-spectrum and high-efficiency antibacterial activity, antimicrobial peptides (AMPs) and their functions have been studied in the field of drug discovery. Using biological experiments to detect the AMPs and corresponding activities req...
Humans Neural Networks, Computer Computational Biology Drug Discovery Antimicrobial Peptides Deep Learning
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Hyb_SEnc: An Antituberculosis Peptide Predictor Based on a Hybrid Feature Vector and Stacked Ensemble Learning.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Tuberculosis has plagued mankind since ancient times, and the struggle between humans and tuberculosis continues. Mycobacterium tuberculosis is the leading cause of tuberculosis, infecting nearly one-third of the world's population. The rise of pepti...
Mycobacterium tuberculosis Humans Ensemble Learning Machine Learning Antitubercular Agents Peptides Tuberculosis Computational Biology Algorithms
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KGRLFF: Detecting Drug-Drug Interactions Based on Knowledge Graph Representation Learning and Feature Fusion.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Accurate prediction of drug-drug interactions (DDIs) plays an important role in improving the efficiency of drug development and ensuring the safety of combination therapy. Most existing models rely on a single source of information to predict DDIs, ...
Algorithms Humans Computational Biology Machine Learning Drug Interactions
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