AIMC Topic: Databases, Protein

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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 Machine Learning Databases, Protein Algorithms Computational Biology Humans
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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 Neural Networks, Computer Databases, Protein Proteins Sequence Analysis, Protein 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 Algorithms Binding Sites Protein Binding Ligands Neural Networks, Computer Computational Biology 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...
Models, Molecular Protein Conformation Proteins Databases, Protein Deep Learning Algorithms Computational Biology
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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...
Proteins Databases, Protein Binding Sites Protein Interaction Maps Computational Biology Protein Interaction Mapping Neural Networks, Computer Algorithms Humans
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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...
Neural Networks, Computer Computational Biology Proteins Humans Binding Sites Databases, Protein Adenosine Triphosphate
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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, ...
Neural Networks, Computer Databases, Protein Algorithms Computational Biology Humans Proteins Deep Learning Protein Interaction Mapping
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Structure-Aware Graph Attention Diffusion Network for Protein-Ligand Binding Affinity Prediction.

IEEE transactions on neural networks and learning systems Dec 2, 2024
Accurate prediction of protein-ligand binding affinities can significantly advance the development of drug discovery. Several graph neural network (GNN)-based methods learn representations of protein-ligand complexes via modeling intermolecule intera...
Humans Neural Networks, Computer Algorithms Proteins Databases, Protein Drug Discovery Ligands Protein Binding
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Ion channel classification through machine learning and protein language model embeddings.

Journal of integrative bioinformatics Nov 25, 2024
Ion channels are critical membrane proteins that regulate ion flux across cellular membranes, influencing numerous biological functions. The resource-intensive nature of traditional wet lab experiments for ion channel identification has led to an inc...
Support Vector Machine Databases, Protein Algorithms Computational Biology Ion Channels Humans Neural Networks, Computer Machine Learning
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Improved Prediction of Ligand-Protein Binding Affinities by Meta-modeling.

Journal of chemical information and modeling Nov 22, 2024
The accurate screening of candidate drug ligands against target proteins through computational approaches is of prime interest to drug development efforts. Such virtual screening depends in part on methods to predict the binding affinity between liga...
Protein Binding Molecular Docking Simulation Databases, Protein Proteins Deep Learning Ligands
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