AIMC Topic: Proteins

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MambaPhase: deep learning for liquid-liquid phase separation protein classification.

Briefings in bioinformatics May 3, 2025
Liquid-liquid phase separation plays a critical role in cellular processes, including protein aggregation and RNA metabolism, by forming membraneless subcellular structures. Accurate identification of phase-separated proteins is essential for underst...
Proteins Phase Separation Humans Deep Learning
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Gated-GPS: enhancing protein-protein interaction site prediction with scalable learning and imbalance-aware optimization.

Briefings in bioinformatics May 1, 2025
In protein-protein interaction site (PPIS) prediction, existing machine learning models struggle with small datasets, limiting their predictive accuracy for unseen proteins. Additionally, class imbalance in protein complexes, where binding residues c...
Computational Biology Proteins Algorithms Protein Binding Protein Interaction Mapping Databases, Protein Humans Binding Sites Machine Learning
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RLEAAI: improving antibody-antigen interaction prediction using protein language model and sequence order information.

Briefings in bioinformatics May 1, 2025
Antibody-antigen interactions (AAIs) are a pervasive phenomenon in the natural and are instrumental in the design of antibody-based drugs. Despite the emergence of various deep learning-based methods aimed at enhancing the accuracy of AAIs prediction...
Humans Neural Networks, Computer Proteins Antibodies Antigen-Antibody Reactions Deep Learning Computational Biology Software Algorithms
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NNKcat: deep neural network to predict catalytic constants (Kcat) by integrating protein sequence and substrate structure with enhanced data imbalance handling.

Briefings in bioinformatics May 1, 2025
Catalytic constant (Kcat) is to describe the efficiency of catalyzing reactions. The Kcat value of an enzyme-substrate pair indicates the rate an enzyme converts saturated substrates into product during the catalytic process. However, it is challengi...
Neural Networks, Computer Algorithms Catalysis Amino Acid Sequence Substrate Specificity Computational Biology Proteins
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Scoring protein-ligand binding structures through learning atomic graphs with inter-molecular adjacency.

PLoS computational biology May 1, 2025
With a burgeoning number of artificial intelligence (AI) applications in various fields, biomolecular science has also given a big welcome to advanced AI techniques in recent years. In this broad field, scoring a protein-ligand binding structure to o...
Computational Biology Binding Sites Proteins Deep Learning Algorithms Ligands Protein Binding Drug Discovery Protein Conformation Models, Molecular
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PackPPI: An integrated framework for protein-protein complex side-chain packing and ΔΔG prediction based on diffusion model.

Protein science : a publication of the Protein Society May 1, 2025
Deep learning methods have played an increasingly pivotal role in advancing side-chain packing and mutation effect prediction (ΔΔG) for protein complexes. Although these two tasks are inherently closely related, they are typically treated separately ...
Databases, Protein Models, Molecular Software Protein Conformation Computational Biology Proteins Algorithms Deep Learning
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H2GnnDTI: hierarchical heterogeneous graph neural networks for drug-target interaction prediction.

Bioinformatics (Oxford, England) Mar 29, 2025
MOTIVATION: Identifying drug-target interactions (DTIs) is a crucial step in drug repurposing and drug discovery. The significant increase in demand and the expensive nature for experimentally identifying DTIs necessitate computational tools for auto...
Neural Networks, Computer Proteins Drug Repositioning Graph Neural Networks Drug Discovery Pharmaceutical Preparations Computational Biology Software Algorithms
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[Research progress in mechanism models and artificial intelligence models for protein expression systems].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology Mar 25, 2025
Proteins are the basic building blocks of life. Studying the protein expression mechanism is essential for understanding the cellular organization principles and the development of biotechnology. Protein expression, involving transcription, translati...
Algorithms Proteins Artificial Intelligence Protein Biosynthesis
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[Intelligent mining, engineering, and design of proteins].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology Mar 25, 2025
Natural components serve the survival instincts of cells that are obtained through long-term evolution, while they often fail to meet the demands of engineered cells for efficiently performing biological functions in special industrial environments. ...
Protein Engineering Enzymes Proteins Data Mining Machine Learning Algorithms Computational Biology Artificial Intelligence
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[Artificial intelligence-enhanced physics-based computational modeling technologies for proteins].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology Mar 25, 2025
Computational modeling is an invaluable tool for mechanism analysis, directed engineering, and rational design of biological parts, metabolic networks, and even cellular systems. It can provide new technological solutions to address biological challe...
Artificial Intelligence Computer Simulation Physics Proteins
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