Details
| Translated title of the contribution | Model development and machine learning increase protein yield |
|---|---|
| Original language | German |
| Pages (from-to) | 262-264 |
| Number of pages | 3 |
| Journal | BioSpektrum |
| Volume | 26 |
| Issue number | 3 |
| Early online date | 14 May 2020 |
| Publication status | Published - May 2020 |
| Externally published | Yes |
Abstract
Heterologous expression of genes requires their adaptation to the host organism to achieve adequate protein synthesis rates. Typically codons are adjusted to resemble those seen in highly expressed genes of the host organism which lacks a deeper understanding of codon optimality. The codon-specific elongation model (COSEM) identifies optimal codon choices by simulating ribosome dynamics during mRNA translation. COSEM is used in combination with machine learning techniques to predict protein abundance and to optimize codon usage.
ASJC Scopus subject areas
- Biochemistry, Genetics and Molecular Biology(all)
- Biotechnology
- Biochemistry, Genetics and Molecular Biology(all)
- Molecular Biology
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In: BioSpektrum, Vol. 26, No. 3, 05.2020, p. 262-264.
Research output: Contribution to journal › Review article › Research › peer review
}
TY - JOUR
T1 - Modellentwicklung und maschinelles Lernen erhöhen die Proteinausbeute
AU - Trösemeier, Jan Hendrik
AU - Rudorf, Sophia
AU - Lößner, Holger
AU - Hofner, Benjamin
AU - Kamp, Christel
N1 - Publisher Copyright: © 2020, Die Autoren.
PY - 2020/5
Y1 - 2020/5
N2 - Heterologous expression of genes requires their adaptation to the host organism to achieve adequate protein synthesis rates. Typically codons are adjusted to resemble those seen in highly expressed genes of the host organism which lacks a deeper understanding of codon optimality. The codon-specific elongation model (COSEM) identifies optimal codon choices by simulating ribosome dynamics during mRNA translation. COSEM is used in combination with machine learning techniques to predict protein abundance and to optimize codon usage.
AB - Heterologous expression of genes requires their adaptation to the host organism to achieve adequate protein synthesis rates. Typically codons are adjusted to resemble those seen in highly expressed genes of the host organism which lacks a deeper understanding of codon optimality. The codon-specific elongation model (COSEM) identifies optimal codon choices by simulating ribosome dynamics during mRNA translation. COSEM is used in combination with machine learning techniques to predict protein abundance and to optimize codon usage.
UR - http://www.scopus.com/inward/record.url?scp=85085061203&partnerID=8YFLogxK
U2 - 10.1007/s12268-020-1369-3
DO - 10.1007/s12268-020-1369-3
M3 - Übersichtsarbeit
AN - SCOPUS:85085061203
VL - 26
SP - 262
EP - 264
JO - BioSpektrum
JF - BioSpektrum
SN - 0947-0867
IS - 3
ER -