Results 251 to 260 of about 273,398 (272)

Cellular and Biophysical Applications of Genetic Code Expansion

Chemical Reviews
Despite their diverse functions, proteins are inherently constructed from a limited set of building blocks. These compositional constraints pose significant challenges to protein research and its practical applications. Strategically manipulating the cellular protein synthesis system to incorporate novel building blocks has emerged as a critical ...
Han Bin Yi, Seungeun Lee, Kyungdeok Seo, Hyeongjo Kim, Minah Kim, Hyun Soo Lee   +5 more
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Genetic Code Expansion in Mammalian Cells

2019
Proteins in nature are synthesized from a conservative set of 20 canonical amino acids, limiting the chemical space of biological systems. Over the last few decades, scientists have developed methods to expand the genetic code of living organisms, introducing new, non-canonical amino acids with diverse chemistries into proteins.
openaire   +1 more source

An expanded lexicon for the ubiquitin code

Nature Reviews Molecular Cell Biology, 2022
Ivan Đikić, Brenda A Schulman
exaly  

The tubulin code and its role in controlling microtubule properties and functions

Nature Reviews Molecular Cell Biology, 2020
Carsten Janke, Maria M Magiera
exaly  

Genetic code flexibility in microorganisms: novel mechanisms and impact on physiology

Nature Reviews Microbiology, 2015
Jiqiang Ling, Patrick O'Donoghue, Dieter Soll   +2 more
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Is there a code embedded in proteins that is based on post-translational modifications?

Nature Reviews Molecular Cell Biology, 2008
Danny Reinberg
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The code and beyond: transcription regulation by the RNA polymerase II carboxy-terminal domain

Nature Reviews Molecular Cell Biology, 2017
Kevin M Harlen, L Stirling Churchman
exaly  

Hijacking endogenous mRNA for genetic code expansion

Nature Chemical Biology
Tomohiro Doura, Yuma Matsuoka, Shigeki Kiyonaka   +2 more
openaire   +2 more sources

Rewiring the keyboard: evolvability of the genetic code

Nature Reviews Genetics, 2001
Laura F Landweber
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A Survey of Machine Learning for Big Code and Naturalness

ACM Computing Surveys, 2019
Miltiadis Allamanis, Earl T Barr
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