Selection on codon bias.

By Ruth Hershberg, D. Petrov. Annual Review of Genetics, 2008

1,011 citations recorded by the source corpus.

Subfields: Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/8087d28454eb5f091ecc9be575293b19d40dd028

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. Dieter Söll
2. Nico J. Claassens
3. Zhang Zhang
4. Tessa E. F. Quax
5. J. van der Oost

In Plant Science

1. Zhang Zhang
2. J. van der Oost

Citations in the corpus

• KaKs_Calculator 3.0: Calculating Selective Pressure on Coding and Non-coding Sequences (2021, methodology): “selection [19-21], has been widely adopted for determining the strength and type of selection 80 operated on coding sequences [22-27].”
• BRAKER3: Fully automated genome annotation using RNA-seq and protein evidence with GeneMark-ETP, AUGUSTUS and TSEBRA (2023, neutral): “However, highly expressed genes may also be better represented by statistical models of gene finding, e.g. because preferred codons may make translation more efficient (Hershberg and Petrov, 2008).”
• Codon Bias as a Means to Fine-Tune Gene Expression (2015, background): “Two not mutually exclusive explanations on the evolution of this bias have been formulated: (1) non-random-ness of mutation and (2) selection for codon bias (Hershberg and Petrov, 2008).”