Antibody-antigen binding prediction
2 papers with code • 1 benchmarks • 0 datasets
Antibody-antigen binding prediction involves using computational or experimental methods to assess how well an antibody interacts with its target antigen. This can be done by analyzing features such as sequence, structure, and physicochemical properties. These predictions aid in designing therapeutic antibodies, vaccines, and diagnostic tests. Validation through experimental assays ensures the accuracy of the predictions and their applicability in biomedical research and development.
Benchmarks
These leaderboards are used to track progress in Antibody-antigen binding prediction
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Most implemented papers
A large-scale systematic survey reveals recurring molecular features of public antibody responses to SARS-CoV-2
nicwulab/HA_Abs
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Immunity 2022
Global research to combat the COVID-19 pandemic has led to the isolation and characterization of thousands of human antibodies to the SARS-CoV-2 spike protein, providing an unprecedented opportunity to study the antibody response to a single antigen.
Deep learning-based rapid generation of broadly reactive antibodies against SARS-CoV-2 and its Omicron variant
jianqingzheng/XBCR-net
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Cell Research 2022
The COVID-19 pandemic has been ongoing for nearly two and half years, and new variants of concern (VOCs) of SARS-CoV-2 continue to emerge, which urges the development of broadly neutralizing antibodies.
