AIMC Topic: Antigen-Antibody Reactions
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DeepInterAware: Deep Interaction Interface-Aware Network for Improving Antigen-Antibody Interaction Prediction from Sequence Data.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Feb 11, 2025
Identifying interactions between candidate antibodies and target antigens is a key step in developing effective human therapeutics. The antigen-antibody interaction (AAI) occurs at the structural level, but the limited structure data poses a signific...
Domain-Scan: Combinatorial Sero-Diagnosis of Infectious Diseases Using Machine Learning.
Frontiers in immunology
Feb 10, 2021
The presence of pathogen-specific antibodies in an individual's blood-sample is used as an indication of previous exposure and infection to that specific pathogen (e.g., virus or bacterium). Measurement of the diagnostic antibodies is routinely achie...
HIV Core Protein p24
Amino Acid Sequence
HIV Antibodies
Hepatitis C Antigens
Oligonucleotides
Genetic Vectors
HIV Envelope Protein gp160
Polymerase Chain Reaction
Epitopes
Antigen-Antibody Reactions
Base Sequence
Hepatitis C Antibodies
High-Throughput Nucleotide Sequencing
AIDS Serodiagnosis
DNA, Recombinant
HIV Infections
Machine Learning
DNA Barcoding, Taxonomic
Peptide Fragments
Peptide Library
Communicable Diseases
Serologic Tests
Hepatitis C
Humans
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...
RLEAAI: improving antibody-antigen interaction prediction using protein language model and sequence order information.
Briefings in bioinformatics
May 1, 2025
Antibody-antigen interactions (AAIs) are a pervasive phenomenon in the natural and are instrumental in the design of antibody-based drugs. Despite the emergence of various deep learning-based methods aimed at enhancing the accuracy of AAIs prediction...
In silico proof of principle of machine learning-based antibody design at unconstrained scale.
mAbs
Jan 1, 2022
Generative machine learning (ML) has been postulated to become a major driver in the computational design of antigen-specific monoclonal antibodies (mAb). However, efforts to confirm this hypothesis have been hindered by the infeasibility of testing ...
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