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Current Opinion in Biotechnology
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November 14, 2025
Building trust in automated experimentation: uncertainty quantification in the era of high-throughput biolabs
Wolfgang Wiechert, Laura M Helleckes, Katharina Nöh
Trends in Biotechnology
|
December 1, 2022
Machine learning in bioprocess development: from promise to practice
Laura M Helleckes, Johannes Hemmerich, Wolfgang Wiechert, et al.
Biotechnology Journal
|
July 12, 2024
Novel calibration design improves knowledge transfer across products for the characterization of pharmaceutical bioprocesses
Laura M Helleckes, Claus Wirnsperger, Jakub Polak, et al.
Microbial Cell Factories
|
July 14, 2023
From frozen cell bank to product assay: high-throughput strain characterisation for autonomous Design-Build-Test-Learn cycles
Laura M Helleckes, Debora Puchta, Hannah Czech, et al.
Biotechnology and Bioengineering
|
January 8, 2026
A Guide to Bayesian Optimization in Bioprocess Engineering
Maximilian Siska, Emma Pajak, Katrin Rosenthal, et al.
Biotechnology and Bioengineering
|
October 13, 2022
Explore or exploit? A model-based screening strategy for PETase secretion by Corynebacterium glutamicum
Laura M Helleckes, Carolin Müller, Tim Griesbach, et al.
Applied Microbiology and Biotechnology
|
June 27, 2022
Accelerated strain construction and characterization of C. glutamicum protein secretion by laboratory automation
Carolin Müller, Patrick J Bakkes, Patrick Lenz, et al.
Biotechnology Progress
|
July 26, 2024
Quantification of nisin concentration from fluorescence-based antimicrobial activity assay using Bayesian calibration
Valentin Steier, Michael Osthege, Laura M Helleckes, et al.
Plos Computational Biology
|
November 27, 2023
Why are different estimates of the effective reproductive number so different? A case study on COVID-19 in Germany
Elisabeth K Brockhaus, Daniel Wolffram, Tanja Stadler, et al.
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of 1
Search research articles
Search
Showing results (1-10 of 9) with videos related to
Sort By:
Page
of 1
Current Opinion in Biotechnology
|
November 14, 2025
Building trust in automated experimentation: uncertainty quantification in the era of high-throughput biolabs
Wolfgang Wiechert, Laura M Helleckes, Katharina Nöh
Trends in Biotechnology
|
December 1, 2022
Machine learning in bioprocess development: from promise to practice
Laura M Helleckes, Johannes Hemmerich, Wolfgang Wiechert, et al.
Biotechnology Journal
|
July 12, 2024
Novel calibration design improves knowledge transfer across products for the characterization of pharmaceutical bioprocesses
Laura M Helleckes, Claus Wirnsperger, Jakub Polak, et al.
Microbial Cell Factories
|
July 14, 2023
From frozen cell bank to product assay: high-throughput strain characterisation for autonomous Design-Build-Test-Learn cycles
Laura M Helleckes, Debora Puchta, Hannah Czech, et al.
Biotechnology and Bioengineering
|
January 8, 2026
A Guide to Bayesian Optimization in Bioprocess Engineering
Maximilian Siska, Emma Pajak, Katrin Rosenthal, et al.
Biotechnology and Bioengineering
|
October 13, 2022
Explore or exploit? A model-based screening strategy for PETase secretion by Corynebacterium glutamicum
Laura M Helleckes, Carolin Müller, Tim Griesbach, et al.
Applied Microbiology and Biotechnology
|
June 27, 2022
Accelerated strain construction and characterization of C. glutamicum protein secretion by laboratory automation
Carolin Müller, Patrick J Bakkes, Patrick Lenz, et al.
Biotechnology Progress
|
July 26, 2024
Quantification of nisin concentration from fluorescence-based antimicrobial activity assay using Bayesian calibration
Valentin Steier, Michael Osthege, Laura M Helleckes, et al.
Plos Computational Biology
|
November 27, 2023
Why are different estimates of the effective reproductive number so different? A case study on COVID-19 in Germany
Elisabeth K Brockhaus, Daniel Wolffram, Tanja Stadler, et al.
Page
of 1