AIMC Topic: Peptides

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DeepAFP: An effective computational framework for identifying antifungal peptides based on deep learning.

Protein science : a publication of the Protein Society Oct 1, 2023
Fungal infections have become a significant global health issue, affecting millions worldwide. Antifungal peptides (AFPs) have emerged as a promising alternative to conventional antifungal drugs due to their low toxicity and low propensity for induci...
Algorithms Peptides Humans Mycoses alpha-Fetoproteins Antifungal Agents Deep Learning
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Efficient prediction of peptide self-assembly through sequential and graphical encoding.

Briefings in bioinformatics Sep 22, 2023
In recent years, there has been an explosion of research on the application of deep learning to the prediction of various peptide properties, due to the significant development and market potential of peptides. Molecular dynamics has enabled the effi...
Neural Networks, Computer Peptides Amino Acids Computer Simulation Artificial Intelligence
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Ionmob: a Python package for prediction of peptide collisional cross-section values.

Bioinformatics (Oxford, England) Sep 2, 2023
MOTIVATION: Including ion mobility separation (IMS) into mass spectrometry proteomics experiments is useful to improve coverage and throughput. Many IMS devices enable linking experimentally derived mobility of an ion to its collisional cross-section...
Mass Spectrometry Peptides Proteomics Ions Machine Learning Amino Acid Sequence
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MITNet: a fusion transformer and convolutional neural network architecture approach for T-cell epitope prediction.

Briefings in bioinformatics Jul 20, 2023
Classifying epitopes is essential since they can be applied in various fields, including therapeutics, diagnostics and peptide-based vaccines. To determine the epitope or peptide against an antibody, epitope mapping with peptides is the most extensiv...
Amino Acid Sequence Receptors, Antigen, T-Cell Neural Networks, Computer Peptides Epitopes, T-Lymphocyte
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TCRmodel2: high-resolution modeling of T cell receptor recognition using deep learning.

Nucleic acids research Jul 5, 2023
The cellular immune system, which is a critical component of human immunity, uses T cell receptors (TCRs) to recognize antigenic proteins in the form of peptides presented by major histocompatibility complex (MHC) proteins. Accurate definition of the...
Antigens Receptors, Antigen, T-Cell Computer Simulation Deep Learning Peptides Humans
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Deep learning-based multi-functional therapeutic peptides prediction with a multi-label focal dice loss function.

Bioinformatics (Oxford, England) Jun 1, 2023
MOTIVATION: With the great number of peptide sequences produced in the postgenomic era, it is highly desirable to identify the various functions of therapeutic peptides quickly. Furthermore, it is a great challenge to predict accurate multi-functiona...
Humans Deep Learning Software Peptides Neural Networks, Computer
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UniDL4BioPep: a universal deep learning architecture for binary classification in peptide bioactivity.

Briefings in bioinformatics May 19, 2023
Identification of potent peptides through model prediction can reduce benchwork in wet experiments. However, the conventional process of model buildings can be complex and time consuming due to challenges such as peptide representation, feature selec...
Deep Learning Amino Acid Sequence Software Peptides Neural Networks, Computer
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PreTP-2L: identification of therapeutic peptides and their types using two-layer ensemble learning framework.

Bioinformatics (Oxford, England) Apr 3, 2023
MOTIVATION: Therapeutic peptides play an important role in immune regulation. Recently various therapeutic peptides have been used in the field of medical research, and have great potential in the design of therapeutic schedules. Therefore, it is ess...
Peptides Amino Acid Sequence Machine Learning
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ExamPle: explainable deep learning framework for the prediction of plant small secreted peptides.

Bioinformatics (Oxford, England) Mar 1, 2023
MOTIVATION: Plant Small Secreted Peptides (SSPs) play an important role in plant growth, development, and plant-microbe interactions. Therefore, the identification of SSPs is essential for revealing the functional mechanisms. Over the last few decade...
Deep Learning Machine Learning Amino Acids Peptides
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Prediction of anticancer peptides based on an ensemble model of deep learning and machine learning using ordinal positional encoding.

Briefings in bioinformatics Jan 19, 2023
Anticancer peptides (ACPs) are the types of peptides that have been demonstrated to have anticancer activities. Using ACPs to prevent cancer could be a viable alternative to conventional cancer treatments because they are safer and display higher sel...
Peptides Deep Learning Machine Learning Algorithms Neural Networks, Computer
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