AIMC Topic: Antigens

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MVSF-AB: accurate antibody-antigen binding affinity prediction via multi-view sequence feature learning.

Bioinformatics (Oxford, England) May 6, 2025
MOTIVATION: Predicting the binding affinity between antigens and antibodies accurately is crucial for assessing therapeutic antibody effectiveness and enhancing antibody engineering and vaccine design. Traditional machine learning methods have been w...
Machine Learning Algorithms Protein Binding Humans Antibody Affinity Sequence Analysis, Protein Antigen-Antibody Reactions Computational Biology Antibodies Antigens
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ParaSurf: a surface-based deep learning approach for paratope-antigen interaction prediction.

Bioinformatics (Oxford, England) Feb 4, 2025
MOTIVATION: Identifying antibody binding sites, is crucial for developing vaccines and therapeutic antibodies, processes that are time-consuming and costly. Accurate prediction of the paratope's binding site can speed up the development by improving ...
Binding Sites, Antibody Computational Biology Software Models, Molecular Deep Learning Antigens Protein Binding
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AttABseq: an attention-based deep learning prediction method for antigen-antibody binding affinity changes based on protein sequences.

Briefings in bioinformatics May 23, 2024
The optimization of therapeutic antibodies through traditional techniques, such as candidate screening via hybridoma or phage display, is resource-intensive and time-consuming. In recent years, computational and artificial intelligence-based methods ...
Computational Biology Mutation Antibodies Humans Deep Learning Antigen-Antibody Complex Antibody Affinity Amino Acid Sequence Antigens
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Artificial Intelligence-Based Counting Algorithm Enables Accurate and Detailed Analysis of the Broad Spectrum of Spot Morphologies Observed in Antigen-Specific B-Cell ELISPOT and FluoroSpot Assays.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2024
Antigen-specific B-cell ELISPOT and multicolor FluoroSpot assays, in which the membrane-bound antigen itself serves as the capture reagent for the antibodies that B cells secrete, inherently result in a broad range of spot sizes and intensities. The ...
Leukocytes, Mononuclear B-Lymphocytes Antigens Artificial Intelligence Algorithms Enzyme-Linked Immunospot Assay
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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...
Computer Simulation Peptides Deep Learning Receptors, Antigen, T-Cell Antigens Humans
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Vaxi-DL: An Artificial Intelligence-Enabled Platform for Vaccine Development.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2023
Vaccine development is a complex and long process. It involves several steps, including computational studies, experimental analyses, animal model system studies, and clinical trials. This process can be accelerated by using in silico antigen screeni...
Animals Artificial Intelligence Vaccine Development Vaccines Proteins Antigens
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Paragraph-antibody paratope prediction using graph neural networks with minimal feature vectors.

Bioinformatics (Oxford, England) Jan 1, 2023
SUMMARY: The development of new vaccines and antibody therapeutics typically takes several years and requires over $1bn in investment. Accurate knowledge of the paratope (antibody binding site) can speed up and reduce the cost of this process by impr...
Antigens Binding Sites, Antibody Software Antibodies Neural Networks, Computer
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Contemporary Challenges in Clinical Flow Cytometry: Small Samples, Big Data, Little Time.

The journal of applied laboratory medicine Jun 30, 2022
BACKGROUND: Immunophenotypic analysis of cell populations by flow cytometry has an established role in primary diagnosis and disease monitoring of many hematologic diseases. A persistent problem in evaluation of specimens is suboptimal cell counts an...
Humans Artificial Intelligence Immunophenotyping Big Data Antigens Flow Cytometry
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DLAB: deep learning methods for structure-based virtual screening of antibodies.

Bioinformatics (Oxford, England) Jan 3, 2022
MOTIVATION: Antibodies are one of the most important classes of pharmaceuticals, with over 80 approved molecules currently in use against a wide variety of diseases. The drug discovery process for antibody therapeutic candidates however is time- and ...
Deep Learning Antibodies Antigens Software
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Precision immunoprofiling to reveal diagnostic signatures for latent tuberculosis infection and reactivation risk stratification.

Integrative biology : quantitative biosciences from nano to macro Jan 1, 2019
Latent tuberculosis infection (LTBI) is estimated in nearly one quarter of the world's population, and of those immunocompetent and infected ~10% will proceed to active tuberculosis (TB). Current diagnostics cannot definitively identify LTBI and prov...
Antigens Photons Leukocytes, Mononuclear Tuberculin Test Computational Biology Biomarkers Immune System Algorithms Mass Screening Female Cytokines Aged Diagnostic Tests, Routine Middle Aged Immunoassay Humans Prospective Studies Adult Silicon Workflow Machine Learning Risk Assessment Male Latent Tuberculosis Mycobacterium tuberculosis
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