Performance of models on Replay heavy chain data.

Performance of models on Replay heavy chain data.

<p>(A) Site substitution overlap and R-precision. (B) Substitution accuracy of the most probable amino acid at sites of substitution. (C) CSP perplexity.</p>

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Bibliographic Details
Main Author:	Mackenzie M. Johnson (22756552) (author)
Other Authors:	Kevin Sung (12400995) (author), Hugh K. Haddox (3396929) (author), Ashni A. Vora (21093610) (author), Tatsuya Araki (22756555) (author), Gabriel D. Victora (5733094) (author), Yun S. Song (14817761) (author), Julia Fukuyama (4376632) (author), Frederick A. Matsen IV (8212521) (author)
Published:	2025
Subjects:	Biochemistry Genetics Molecular Biology Biotechnology Evolutionary Biology Immunology Cancer Inorganic Chemistry Infectious Diseases Biological Sciences not elsewhere classified specific mouse experiment large data sets integrate evolutionary principles b cell receptors understanding antibody evolution two main perspectives bcrs ): membrane affinity maturation ), nucleotide sequence context protein language models affinity maturation nucleotide context protein sequences molecular evolution language modeling b cells antibody sequences simple nucleotide substantial amount somatic hypermutation road map predictive power precise modeling modest improvement introduce epam incorporating estimates included models improve binding evaluating predictions describe mutation crucial role computational models compared models bound forms benchmarking framework bcr sequences adaptive immunity
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