AIMC Topic: Peptides

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Serum peptide biomarkers by MALDI-TOF MS coupled with machine learning for diagnosis and classification of hepato-pancreato-biliary cancers.

Scientific reports Aug 9, 2025
This study aimed to investigate the potential of peptide mass fingerprints (PMFs) of the serum peptidome using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), in combination with machine learning algorithm...
Machine Learning Female Aged Humans Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Biliary Tract Neoplasms Peptides Male Liver Neoplasms Middle Aged Support Vector Machine Adult Pancreatic Neoplasms Biomarkers, Tumor
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AAGP integrates physicochemical and compositional features for machine learning-based prediction of anti-aging peptides.

Scientific reports Aug 8, 2025
Aging is a natural phenomenon characterized by the loss of normal morphology and physiological functioning of the body, causing wrinkles on the skin, loss of hair, and compromised immune systems. Peptide therapies have emerged as a promising approach...
Humans Machine Learning Algorithms Peptides Aging Computational Biology Antimicrobial Peptides
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HLAIIPred: cross-attention mechanism for modeling the interaction of HLA class II molecules with peptides.

Communications biology Jul 30, 2025
We introduce HLAIIPred, a deep learning model to predict peptides presented by class II human leukocyte antigens (HLAII) on the surface of antigen presenting cells. HLAIIPred is trained using a Transformer-based neural network and a dataset comprisin...
Deep Learning Histocompatibility Antigens Class II Humans Peptides Antigen Presentation
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Integration of pre-trained protein language models with equivariant graph neural networks for peptide toxicity prediction.

BMC biology Jul 28, 2025
BACKGROUND: Peptide-based therapeutics have great potential due to their versatility, high specificity, and suitability for a variety of therapeutic applications. Despite these advantages, the inherent toxicities of some peptides pose challenges in d...
Neural Networks, Computer Peptides Graph Neural Networks
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Applications of enhanced sampling methods to biomolecular self-assembly: a review.

Journal of physics. Condensed matter : an Institute of Physics journal Jul 23, 2025
This review article discusses some common enhanced sampling methods in relation to the process of self-assembly of biomolecules. An introduction to self-assembly and its challenges is covered followed by a brief overview of the methods and analysis f...
Nucleic Acids Polymers Molecular Dynamics Simulation Peptides Proteins Machine Learning
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BPFun: a deep learning framework for bioactive peptide function prediction using multi-label strategy by transformer-driven and sequence rich intrinsic information.

BMC bioinformatics Jul 21, 2025
Bioactive peptides are beneficial or have physiological effects on the life activities of biological organisms. The functions of bioactive peptides are diverse, usually with one or more, so accurately detecting the multiple functions of multi-functio...
Peptides Amino Acid Sequence Deep Learning Computational Biology
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MultiRepPI: a cross-modal feature fusion-based multiple characterization framework for plant peptide-protein interaction prediction.

BMC plant biology Jul 19, 2025
Plant peptide-protein interactions (PepPI) play a crucial role in plant growth, development, immune regulation, and environmental adaptation. However, existing computational methods still face several challenges in PepPI prediction. First, most metho...
Protein Interaction Mapping Peptides Neural Networks, Computer Computational Biology Plant Proteins
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Evaluation of the False Discovery Rate in Library-Free Search by DIA-NN Using Human Proteome.

Journal of proteome research Jul 18, 2025
Recently, deep-learning-based spectral libraries have gained increasing attention. Several data-independent acquisition (DIA) software tools have integrated this feature, known as a library-free search, thereby making DIA analysis more accessible. H...
Deep Learning Software Proteomics Humans Recombinant Proteins Proteome Peptides Tandem Mass Spectrometry Mass Spectrometry Gene Library Chromatography, Liquid
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In Silico tool for predicting, designing and scanning IL-2 inducing peptides.

Scientific reports Jul 16, 2025
Interleukin-2 (IL-2) based immunotherapy has been approved for treating certain types of cancer, as IL-2 plays a crucial role in regulating the immune system. In this study, we developed a method for predicting IL-2-inducing peptides. Our method was ...
Deep Learning Computational Biology Humans Interleukin-2 Computer Simulation Machine Learning Peptides
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A hybrid framework of generative deep learning for antiviral peptide discovery.

Scientific reports Jul 15, 2025
Antiviral peptides (AVPs) hold great potential for combating viral infections, yet their discovery and development remain challenging. In this study, we present a hybrid model combining Wasserstein Generative Adversarial Networks with Gradient Penalt...
Deep Learning Drug Discovery Antiviral Agents Influenza A virus Humans Peptides
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