AIMC Topic: 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...
Algorithms Data Mining Humans Databases, Factual Neural Networks, Computer Biomedical Research Computational Biology
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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 ...
Computational Biology RNA-Binding Proteins Humans Machine Learning Algorithms Epithelial-Mesenchymal Transition Alternative Splicing
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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...
Antimicrobial Peptides Deep Learning Humans Computational Biology Neural Networks, Computer Drug Discovery
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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...
Machine Learning Algorithms Mycobacterium tuberculosis Humans Antitubercular Agents Peptides Ensemble Learning Tuberculosis Computational Biology
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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, ...
Humans Machine Learning Computational Biology Drug Interactions Algorithms
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HGLA: Biomolecular Interaction Prediction Based on Mixed High-Order Graph Convolution With Filter Network via LSTM and Channel Attention.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Predicting biomolecular interactions is significant for understanding biological systems. Most existing methods for link prediction are based on graph convolution. Although graph convolution methods are advantageous in extracting structure informatio...
Protein Interaction Mapping Algorithms Computational Biology Humans Neural Networks, Computer
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Generative Adversarial Network-Based Augmentation With Noval 2-Step Authentication for Anti-Coronavirus Peptide Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
The virus poses a longstanding and enduring danger to various forms of life. Despite the ongoing endeavors to combat viral diseases, there exists a necessity to explore and develop novel therapeutic options. Antiviral peptides are bioactive molecules...
Computational Biology Generative Adversarial Networks Deep Learning Antiviral Agents Humans Neural Networks, Computer Peptides
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Employing Machine Learning Techniques to Detect Protein Function: A Survey, Experimental, and Empirical Evaluations.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
This review article delves deeply into the various machine learning (ML) methods and algorithms employed in discerning protein functions. Each method discussed is assessed for its efficacy, limitations, potential improvements, and future prospects. W...
Algorithms Computational Biology Proteins Humans Machine Learning Databases, Protein
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Improved Fuzzy Cognitive Maps for Gene Regulatory Networks Inference Based on Time Series Data.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Microarray data provide lots of information regarding gene expression levels. Due to the large amount of such data, their analysis requires sufficient computational methods for identifying and analyzing gene regulation networks; however, researchers ...
Gene Regulatory Networks Computational Biology Fuzzy Logic Algorithms Gene Expression Profiling Humans
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Graph Convolutional Network With Self-Supervised Learning for Brain Disease Classification.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Brain functional network (BFN) analysis has become a popular method for identifying neurological diseases at their early stages and revealing sensitive biomarkers related to these diseases. Due to the fact that BFN is a graph with complex structure, ...
Databases, Factual Autism Spectrum Disorder Neural Networks, Computer Algorithms Computational Biology Supervised Machine Learning Brain Diseases Brain Cognitive Dysfunction Humans
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