000009217 001__ 9217
000009217 005__ 20240301092309.0
000009217 0247_ $$2DOI$$a10.6083/fq977v625
000009217 037__ $$aIR
000009217 041__ $$aeng
000009217 245__ $$aCodonify: a recurrent-neural-network based codon optimization tool to improve protein expression
000009217 260__ $$bOregon Health and Science University
000009217 269__ $$a2021
000009217 336__ $$aAbstract
000009217 520__ $$aDesigning synthetic genes for heterologous expression is a keystone of synthetic biology. In protein sequences - as there are 61 sense codons but only 20 standard amino acids - most amino acids are encoded by more than one codon. Although such synonymous codons do not alter the encoded amino acid sequence, they are not redundant. By using certain codons over others, gene expression can be improved by up to 1000 times. Industry-standard codon optimization techniques based on biological indexes replace synonymous codons with the most abundant codon found in the host organism's genome. However, this technique may result in an imbalanced tRNA pool, metabolic stress, and translational error which lead to greater cell toxicity and reduced protein expression. In this research, recurrent neural networks are used to accurately capture sequential and contextual patterns. By predicting synonymous codons based on the sequential information of the host organism, protein expression can be increased while preventing translational error and plasmid toxicity.
000009217 540__ $$fCC BY
000009217 542__ $$fIn copyright - single owner
000009217 650__ $$aGene Expression$$028717
000009217 650__ $$aCodon Usage$$013233
000009217 650__ $$aDeep Learning$$012734
000009217 650__ $$aSynthetic Biology$$039275
000009217 650__ $$aCodon$$016859
000009217 650__ $$aMachine Learning$$011449
000009217 650__ $$aArtificial Intelligence$$015109
000009217 6531_ $$acodon optimization
000009217 6531_ $$aprotein expression
000009217 6531_ $$aheterologous expression
000009217 6531_ $$aneutral network
000009217 7001_ $$aJain, Rishab$$uWestview High School
000009217 711__ $$aResearch Week$$uOregon Health and Science University$$d2021
000009217 8564_ $$95626d698-0e73-4683-bb6e-4613cd93a89e$$s82578$$uhttps://digitalcollections.ohsu.edu/record/9217/files/Jain-Rishab-OHSU-ResearchWeek-2021.pdf
000009217 905__ $$a/rest/prod/fq/97/7v/62/fq977v625
000009217 980__ $$aResearch Week