AIMC Topic: Computational Biology

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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...
Computational Biology Humans Drug Discovery Antimicrobial Peptides Deep Learning Neural Networks, Computer
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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...
Computational Biology Antitubercular Agents Algorithms Peptides Ensemble Learning Tuberculosis Mycobacterium tuberculosis Humans Machine Learning
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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, ...
Computational Biology Drug Interactions Machine Learning Algorithms Humans
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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...
Humans Neural Networks, Computer Protein Interaction Mapping Algorithms Computational Biology
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Diffusing on Two Levels and Optimizing for Multiple Properties: A Novel Approach to Generating Molecules With Desirable Properties.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
In the past decade, Artificial Intelligence (AI) driven drug design and discovery has been a hot research topic in the AI area, where an important branch is molecule generation by generative models, from GAN-based models and VAE-based models to the l...
Drug Discovery Computational Biology Diffusion Algorithms Drug Design Artificial Intelligence
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Machine Learning-Assisted High-Throughput Screening for Anti-MRSA Compounds.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
BACKGROUND: Antimicrobial resistance is a major public health threat, and new agents are needed. Computational approaches have been proposed to reduce the cost and time needed for compound screening.
Drug Evaluation, Preclinical High-Throughput Screening Assays Caenorhabditis elegans Computational Biology Methicillin-Resistant Staphylococcus aureus Animals Microbial Sensitivity Tests Machine Learning Anti-Bacterial Agents
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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...
Deep Learning Antiviral Agents Neural Networks, Computer Peptides Computational Biology Generative Adversarial Networks Humans
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Enhancing Generalizability in Biomedical Entity Recognition: Self-Attention PCA-CLS Model.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
One of the primary tasks in the early stages of data mining involves the identification of entities from biomedical corpora. Traditional approaches relying on robust feature engineering face challenges when learning from available (un-)annotated data...
Biomedical Research Convolutional Neural Networks Computational Biology Data Mining Natural Language Processing Datasets as Topic
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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...
Proteins Databases, Protein Humans Machine Learning Algorithms Computational Biology
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Bi-SeqCNN: A Novel Light-Weight Bi-Directional CNN Architecture for Protein Function Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Deep learning approaches, such as convolution neural networks (CNNs) and deep recurrent neural networks (RNNs), have been the backbone for predicting protein function, with promising state-of-the-art (SOTA) results. RNNs with an in-built ability (i) ...
Proteins Neural Networks, Computer Deep Learning Databases, Protein Algorithms Computational Biology Sequence Analysis, Protein
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