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  Modellentwicklung und maschinelles Lernen erhöhen die Proteinausbeute

Trösemeier, J.-H., Rudorf, S., Lößner, H., Hofner, B., & Kamp, C. (2020). Modellentwicklung und maschinelles Lernen erhöhen die Proteinausbeute. Biospektrum, 26(3), 262-264. doi:10.1007/s12268-020-1369-3.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0006-6C6E-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0006-6C6F-6
Genre: Journal Article

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Trösemeier, Jan-Hendrik, Author
Rudorf, Sophia1, Author              
Lößner, Holger, Author
Hofner, Benjamin, Author
Kamp, Christel, Author
Affiliations:
1Sophia Rudorf, Theorie & Bio-Systeme, Max Planck Institute of Colloids and Interfaces, Max Planck Society, ou_2205637              

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 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.

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Language(s): deu - German
 Dates: 2020-05-142020
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Method: No review
 Identifiers: DOI: 10.1007/s12268-020-1369-3
Other: Trösemeier2020
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Title: Biospektrum
Source Genre: Journal
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Publ. Info: Heidelberg, Germany : Springer Spektrum
Pages: - Volume / Issue: 26 (3) Sequence Number: - Start / End Page: 262 - 264 Identifier: ISSN: 0947-0867