Known highly conserved sites were not typically well described by models.

Known highly conserved sites were not typically well described by models.

<p>(A) The locations of seven highly conserved sites are highlighted in red. (B) Observed and expected number of substitutions at these seven conserved sites for various models.</p>

Saved in:

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
Tags:	Add Tag No Tags, Be the first to tag this record!

Cannot write session to /tmp/vufind_sessions/sess_db3h358jadrdrukt73fbqc1hle