AIMC Topic: Peptides

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The Immunopeptidomics Ontology (ImPO).

Database : the journal of biological databases and curation Jun 7, 2024
The adaptive immune response plays a vital role in eliminating infected and aberrant cells from the body. This process hinges on the presentation of short peptides by major histocompatibility complex Class I molecules on the cell surface. Immunopepti...
Humans Databases, Protein Biological Ontologies Peptides Proteomics
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CELA-MFP: a contrast-enhanced and label-adaptive framework for multi-functional therapeutic peptides prediction.

Briefings in bioinformatics May 23, 2024
Functional peptides play crucial roles in various biological processes and hold significant potential in many fields such as drug discovery and biotechnology. Accurately predicting the functions of peptides is essential for understanding their divers...
Computational Biology Databases, Protein Deep Learning Humans Software Algorithms Peptides
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TP-LMMSG: a peptide prediction graph neural network incorporating flexible amino acid property representation.

Briefings in bioinformatics May 23, 2024
Bioactive peptide therapeutics has been a long-standing research topic. Notably, the antimicrobial peptides (AMPs) have been extensively studied for its therapeutic potential. Meanwhile, the demand for annotating other therapeutic peptides, such as a...
Amino Acids Antimicrobial Peptides Computational Biology Neural Networks, Computer Algorithms Peptides Deep Learning
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Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides.

Briefings in bioinformatics May 23, 2024
With their diverse biological activities, peptides are promising candidates for therapeutic applications, showing antimicrobial, antitumour and hormonal signalling capabilities. Despite their advantages, therapeutic peptides face challenges such as s...
Machine Learning Peptides Humans Artificial Intelligence Drug Discovery Drug Design Computational Biology
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DeepAVP-TPPred: identification of antiviral peptides using transformed image-based localized descriptors and binary tree growth algorithm.

Bioinformatics (Oxford, England) May 2, 2024
MOTIVATION: Despite the extensive manufacturing of antiviral drugs and vaccination, viral infections continue to be a major human ailment. Antiviral peptides (AVPs) have emerged as potential candidates in the pursuit of novel antiviral drugs. These p...
Computational Biology Humans Peptides Machine Learning Antiviral Agents Algorithms Neural Networks, Computer
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MA-PEP: A novel anticancer peptide prediction framework with multimodal feature fusion based on attention mechanism.

Protein science : a publication of the Protein Society Apr 1, 2024
AntiCancer Peptides (ACPs) have emerged as promising therapeutic agents for cancer treatment. The time-consuming and costly nature of wet-lab discriminatory methods has spurred the development of various machine learning and deep learning-based ACP c...
Peptides Machine Learning Benchmarking
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Contrastive learning for enhancing feature extraction in anticancer peptides.

Briefings in bioinformatics Mar 27, 2024
Cancer, recognized as a primary cause of death worldwide, has profound health implications and incurs a substantial social burden. Numerous efforts have been made to develop cancer treatments, among which anticancer peptides (ACPs) are garnering reco...
Machine Learning Algorithms Deep Learning Humans Peptides Computational Biology Neoplasms Antineoplastic Agents
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AACFlow: an end-to-end model based on attention augmented convolutional neural network and flow-attention mechanism for identification of anticancer peptides.

Bioinformatics (Oxford, England) Mar 4, 2024
MOTIVATION: Anticancer peptides (ACPs) have natural cationic properties and can act on the anionic cell membrane of cancer cells to kill cancer cells. Therefore, ACPs have become a potential anticancer drug with good research value and prospect.
Neural Networks, Computer Peptides Cell Membrane
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StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides.

Bioinformatics (Oxford, England) Feb 1, 2024
MOTIVATION: Diabetes is a chronic metabolic disorder that has been a major cause of blindness, kidney failure, heart attacks, stroke, and lower limb amputation across the world. To alleviate the impact of diabetes, researchers have developed the next...
Diabetes Mellitus Amino Acids Deep Learning Humans Peptides Dipeptidyl Peptidase 4
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RPEMHC: improved prediction of MHC-peptide binding affinity by a deep learning approach based on residue-residue pair encoding.

Bioinformatics (Oxford, England) Jan 2, 2024
MOTIVATION: Binding of peptides to major histocompatibility complex (MHC) molecules plays a crucial role in triggering T cell recognition mechanisms essential for immune response. Accurate prediction of MHC-peptide binding is vital for the developmen...
Deep Learning Peptides Histocompatibility Antigens Class I Protein Binding Major Histocompatibility Complex
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