AIMC Topic: Proteins

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Ensemble of local and global information for Protein-Ligand Binding Affinity Prediction.

Computational biology and chemistry Oct 20, 2023
Accurately predicting protein-ligand binding affinities is crucial for determining molecular properties and understanding their physical effects. Neural networks and transformers are the predominant methods for sequence modeling, and both have been s...
Ligands Algorithms Neural Networks, Computer Proteins Protein Binding
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A Review of Machine Learning and Algorithmic Methods for Protein Phosphorylation Site Prediction.

Genomics, proteomics & bioinformatics Oct 19, 2023
Post-translational modifications (PTMs) have key roles in extending the functional diversity of proteins and, as a result, regulating diverse cellular processes in prokaryotic and eukaryotic organisms. Phosphorylation modification is a vital PTM that...
Proteins Protein Processing, Post-Translational Phosphorylation Databases, Protein Animals Computational Biology Algorithms Humans Machine Learning
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Machine learning-based model for accurate identification of druggable proteins using light extreme gradient boosting.

Journal of biomolecular structure & dynamics Oct 18, 2023
The identification of druggable proteins (DPs) is significant for the development of new drugs, personalized medicine, understanding of disease mechanisms, drug repurposing, and economic benefits. By identifying new druggable targets, researchers can...
Proteins Amino Acids Computational Biology Position-Specific Scoring Matrices Machine Learning Humans Drug Discovery Algorithms
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ResCNNT-fold: Combining residual convolutional neural network and Transformer for protein fold recognition from language model embeddings.

Computers in biology and medicine Oct 17, 2023
A comprehensive understanding of protein functions holds significant promise for disease research and drug development, and proteins with analogous tertiary structures tend to exhibit similar functions. Protein fold recognition stands as a classical ...
Computational Biology Proteins Neural Networks, Computer Humans Databases, Protein Protein Folding Sequence Analysis, Protein
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Naive Prediction of Protein Backbone Phi and Psi Dihedral Angles Using Deep Learning.

Molecules (Basel, Switzerland) Oct 12, 2023
Protein structure prediction represents a significant challenge in the field of bioinformatics, with the prediction of protein structures using backbone dihedral angles recently achieving significant progress due to the rise of deep neural network re...
Protein Structure, Secondary Proteins Amino Acid Sequence Deep Learning Neural Networks, Computer
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ResBiGAAT: Residual Bi-GRU with attention for protein-ligand binding affinity prediction.

Computational biology and chemistry Oct 11, 2023
Protein-ligand interaction plays a crucial role in drug discovery, facilitating efficient drug development and enabling drug repurposing. Several computational algorithms, such as Graph Neural Networks and Convolutional Neural Networks, have been pro...
Proteins Ligands Protein Binding Neural Networks, Computer Deep Learning Algorithms
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PointDE: Protein Docking Evaluation Using 3D Point Cloud Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2023
Protein-protein interactions (PPIs) play essential roles in many vital movements and the determination of protein complex structure is helpful to discover the mechanism of PPI. Protein-protein docking is being developed to model the structure of the ...
Proteins Neural Networks, Computer
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Predicting Protein-Protein Interactions Using Sequence and Network Information via Variational Graph Autoencoder.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2023
Protein-protein interactions (PPIs) play a critical role in the proteomics study, and a variety of computational algorithms have been developed to predict PPIs. Though effective, their performance is constrained by high false-positive and false-negat...
Algorithms Protein Interaction Mapping Proteins Neural Networks, Computer
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Prediction of Protein-Protein Interactions Using Vision Transformer and Language Model.

IEEE/ACM transactions on computational biology and bioinformatics Oct 9, 2023
The knowledge of protein-protein interaction (PPI) helps us to understand proteins' functions, the causes and growth of several diseases, and can aid in designing new drugs. The majority of existing PPI research has relied mainly on sequence-based ap...
Amino Acid Sequence Proteins Saccharomyces cerevisiae Neural Networks, Computer Multiomics Humans
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E2EDA: Protein Domain Assembly Based on End-to-End Deep Learning.

Journal of chemical information and modeling Oct 3, 2023
With the development of deep learning, almost all single-domain proteins can be predicted at experimental resolution. However, the structure prediction of multi-domain proteins remains a challenge. Achieving end-to-end protein domain assembly and fur...
Proteins Protein Domains Deep Learning
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