AIMC Topic: Proteins

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An End-to-End Knowledge Graph Fused Graph Neural Network for Accurate Protein-Protein Interactions Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Protein-protein interactions (PPIs) are essential to understanding cellular mechanisms, signaling networks, disease processes, and drug development, as they represent the physical contacts and functional associations between proteins. Recent advances...
Computational Biology Proteins Protein Interaction Mapping Graph Neural Networks Databases, Protein Algorithms Protein Interaction Maps Humans Neural Networks, Computer
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A Protein-Context Enhanced Master Slave Framework for Zero-Shot Drug Target Interaction Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Drug Target Interaction (DTI) prediction plays a crucial role in in-silico drug discovery, especially for deep learning (DL) models. Along this line, existing methods usually first extract features from drugs and target proteins, and use drug-target ...
Drug Discovery Deep Learning Computational Biology Humans Algorithms Ligands Proteins Databases, Protein
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MMD-DTA: A Multi-Modal Deep Learning Framework for Drug-Target Binding Affinity and Binding Region Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
The prediction of drug-target affinity (DTA) plays a crucial role in drug development and the identification of potential drug targets. In recent years, computer-assisted DTA prediction has emerged as a significant approach in this field. In this stu...
Pharmaceutical Preparations Binding Sites Protein Binding Computational Biology Proteins Drug Discovery Deep Learning Humans Neural Networks, Computer
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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...
Machine Learning Algorithms Humans Databases, Protein Computational Biology Proteins
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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) ...
Deep Learning Computational Biology Databases, Protein Sequence Analysis, Protein Proteins Neural Networks, Computer Algorithms
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Intra-Inter Graph Representation Learning for Protein-Protein Binding Sites Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Graph neural networks have drawn increasing attention and achieved remarkable progress recently due to their potential applications for a large amount of irregular data. It is a natural way to represent protein as a graph. In this work, we focus on p...
Proteins Databases, Protein Binding Sites Ligands Algorithms Protein Binding Computational Biology Neural Networks, Computer Machine Learning
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Prediction of Inter-Residue Multiple Distances and Exploration of Protein Multiple Conformations by Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
AlphaFold2 has achieved a major breakthrough in end-to-end prediction for static protein structures. However, protein conformational change is considered to be a key factor in protein biological function. Inter-residue multiple distances prediction i...
Proteins Databases, Protein Models, Molecular Deep Learning Computational Biology Protein Conformation Algorithms
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RGCNPPIS: A Residual Graph Convolutional Network for Protein-Protein Interaction Site Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Accurate identification of protein-protein interaction (PPI) sites is crucial for understanding the mechanisms of biological processes, developing PPI networks, and detecting protein functions. Currently, most computational methods primarily concentr...
Neural Networks, Computer Algorithms Protein Interaction Maps Humans Databases, Protein Binding Sites Protein Interaction Mapping Computational Biology Proteins
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ATP_mCNN: Predicting ATP binding sites through pretrained language models and multi-window neural networks.

Computers in biology and medicine Dec 8, 2024
Adenosine triphosphate plays a vital role in providing energy and enabling key cellular processes through interactions with binding proteins. The increasing amount of protein sequence data necessitates computational methods for identifying binding si...
Adenosine Triphosphate Binding Sites Humans Neural Networks, Computer Proteins Databases, Protein Computational Biology
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Protein-protein interaction detection using deep learning: A survey, comparative analysis, and experimental evaluation.

Computers in biology and medicine Dec 6, 2024
This survey paper provides a comprehensive analysis of various Deep Learning (DL) techniques and algorithms for detecting protein-protein interactions (PPIs). It examines the scalability, interpretability, accuracy, and efficiency of each technique, ...
Humans Neural Networks, Computer Algorithms Proteins Databases, Protein Protein Interaction Mapping Deep Learning Computational Biology
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