PFSDS015
iStrainML: Improving Strain Engineering by Machine Learning
| Grant period | 7 months |
| Funding body | Exploratory Research Space der RWTH Aachen |
| ERS | |
| Identifier | G:(DE-82)EXS-PF-PFSDS015 |
All known publications ...
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Journal Article
Insight to Gene Expression From Promoter Libraries With the Machine Learning Workflow Exp2Ipynb
Frontiers in bioinformatics 1, 747428 (2021) [10.3389/fbinf.2021.747428]
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Journal Article
Genome-scale model reconstruction of the methylotrophic yeast Ogataea polymorpha
BMC biotechnology 21(23), 1-8 (2021) [10.1186/s12896-021-00675-w]
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Preprint
Exp2Ipynb : A general machine-learning workflow for the analysis of promoter libraries
10 Seiten (2020) [10.1101/2020.12.14.422740]
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Poster
Promoter design workflow for defined cross-host expression in P. taiwanensis and E. coli
EMBO Symposium "Engineering meets evolution: Designing biological systems", EMBO Symposium, ChennaiChennai, India, 29 Jan 2020 - 2 Feb 2020
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Journal Article (Review Article)/Contribution to a book
Machine Learning Applications for Mass Spectrometry-Based Metabolomics
Metabolites : open access journal 10(6), 243 (2020) [10.3390/metabo10060243] special issue: "Special Issue "Metabolic Engineering and Synthetic Biology" / Special Issue Editors: Prof. Dr. Lars M. Blank, Guest Editor; Dr. An N.T. Phan, Guest Editor . - Volume 2"
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Conference Presentation (After Call)
Tool Development for Promoter Sequence Prediction with Defined Activity for sigma70-driven Gene Expression
German Conference on Synthetic Biology, GCSB, AachenAachen, Germany, 11 Sep 2019 - 13 Sep 2019
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