Quantifying and understanding the fitness effects of protein mutations: Laboratory versus nature

By J. Boucher, Daniel N. A. Bolon, Dan S. Tawfik. 2016

93 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Grant Goldman
2. Charlotte H. Wang
3. Vasilis Ntranos
4. Chun Jimmie Ye
5. Nadav Brandes

Citations in the corpus

• Genome-wide prediction of disease variants with a deep protein language model (2022, background): “However, their current limited scale precludes genomewide experiments, and the specific cellular phenotypes measured are imperfect proxies for the clinical phenotype of interest (e.g., disease risk or therapeutic response) [13, 14].”