AIMC Topic: Epitope Mapping
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Integrating machine learning to advance epitope mapping.
Frontiers in immunology
Sep 30, 2024
Identifying epitopes, or the segments of a protein that bind to antibodies, is critical for the development of a variety of immunotherapeutics and diagnostics. In vaccine design, the intent is to identify the minimal epitope of an antigen that can el...
Integrated structural proteomics and machine learning-guided mapping of a highly protective precision vaccine against mycoplasma pulmonis.
International immunopharmacology
Aug 16, 2024
Mycoplasma pulmonis (M. pulmonis) is an emerging respiratory infection commonly linked to prostate cancer, and it is classified under the group of mycoplasmas. Improved management of mycoplasma infections is essential due to the frequent ineffectiven...
Epitope Identification of an mGlu5 Receptor Nanobody Using Physics-Based Molecular Modeling and Deep Learning Techniques.
Journal of chemical information and modeling
Feb 29, 2024
The world has witnessed a revolution in therapeutics with the development of biological medicines such as antibodies and antibody fragments, notably nanobodies. These nanobodies possess unique characteristics including high specificity and modulatory...
Improvement of Neoantigen Identification Through Convolution Neural Network.
Frontiers in immunology
May 25, 2021
Accurate prediction of neoantigens and the subsequent elicited protective anti-tumor response are particularly important for the development of cancer vaccine and adoptive T-cell therapy. However, current algorithms for predicting neoantigens are lim...
Introducing of an integrated artificial neural network and Chou's pseudo amino acid composition approach for computational epitope-mapping of Crimean-Congo haemorrhagic fever virus antigens.
International immunopharmacology
Nov 24, 2019
This study was aimed to introduce a novel algorithm for determining linear B- and T-cell epitopes from Crimean-Congo haemorrhagic fever virus (CCHFV) antigens. To this end, 387 approved B- and T-cell epitopes, as well as 331 non-epitope peptides from...
Hemorrhagic Fever, Crimean
Histocompatibility Antigens Class II
Epitopes, B-Lymphocyte
Epitope Mapping
Hemorrhagic Fever Virus, Crimean-Congo
Viral Proteins
Antigens, Viral
Protein Structure, Tertiary
Neural Networks, Computer
Epitopes, T-Lymphocyte
Molecular Docking Simulation
Peptide Library
Computational Biology
Support Vector Machine
Amino Acid Sequence
Datasets as Topic
Humans
Accurate Prediction for Antibody Resistance of Clinical HIV-1 Isolates.
Scientific reports
Oct 11, 2019
Broadly neutralizing antibodies (bNAbs) targeting the HIV-1 envelope glycoprotein (Env) have promising utility in prevention and treatment of HIV-1 infection, and several are currently undergoing clinical trials. Due to the high sequence diversity an...
Improvement of Epitope Prediction Using Peptide Sequence Descriptors and Machine Learning.
International journal of molecular sciences
Sep 5, 2019
In this work, we improved a previous model used for the prediction of proteomes as new B-cell epitopes in vaccine design. The predicted epitope activity of a queried peptide is based on its sequence, a known reference epitope sequence under specific ...
Staged heterogeneity learning to identify conformational B-cell epitopes from antigen sequences.
BMC genomics
Mar 14, 2017
BACKGROUND: The broad heterogeneity of antigen-antibody interactions brings tremendous challenges to the design of a widely applicable learning algorithm to identify conformational B-cell epitopes. Besides the intrinsic heterogeneity introduced by di...
Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology.
International journal of molecular sciences
Feb 1, 2017
Reverse vaccinology (RV) is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of...
AI-augmented physics-based docking for antibody-antigen complex prediction.
Bioinformatics (Oxford, England)
Mar 29, 2025
MOTIVATION: Predicting the structure of antibody-antigen complexes is a challenging task with significant implications for the design of better antibody therapeutics. However, the levels of success have remained dauntingly low, particularly when high...
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