Examination of a genetic algorithm for the application in high-throughput downstream process development

2012 ◽  
Vol 7 (10) ◽  
pp. 1203-1215 ◽  
Author(s):  
Katrin Treier ◽  
Annette Berg ◽  
Patrick Diederich ◽  
Katharina Lang ◽  
Anna Osberghaus ◽  
...  
2016 ◽  
Vol 1464 ◽  
pp. 1-11 ◽  
Author(s):  
Sarah Zimmermann ◽  
Sarah Gretzinger ◽  
Marie-Luise Schwab ◽  
Christian Scheeder ◽  
Philipp K. Zimmermann ◽  
...  

2016 ◽  
Vol 12 (2) ◽  
pp. 1600587 ◽  
Author(s):  
Sarah Zimmermann ◽  
Christian Scheeder ◽  
Philipp K Zimmermann ◽  
Are Bogsnes ◽  
Mattias Hansson ◽  
...  

2021 ◽  
pp. 2000641
Author(s):  
Krishana C. Gulla ◽  
Zachary J. Schneiderman ◽  
Sarah E. O'Connell ◽  
Gabriel F. Arias ◽  
Nicole L. Cibelli ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mathias Fink ◽  
Monika Cserjan-Puschmann ◽  
Daniela Reinisch ◽  
Gerald Striedner

AbstractTremendous advancements in cell and protein engineering methodologies and bioinformatics have led to a vast increase in bacterial production clones and recombinant protein variants to be screened and evaluated. Consequently, an urgent need exists for efficient high-throughput (HTP) screening approaches to improve the efficiency in early process development as a basis to speed-up all subsequent steps in the course of process design and engineering. In this study, we selected the BioLector micro-bioreactor (µ-bioreactor) system as an HTP cultivation platform to screen E. coli expression clones producing representative protein candidates for biopharmaceutical applications. We evaluated the extent to which generated clones and condition screening results were transferable and comparable to results from fully controlled bioreactor systems operated in fed-batch mode at moderate or high cell densities. Direct comparison of 22 different production clones showed great transferability. We observed the same growth and expression characteristics, and identical clone rankings except one host-Fab-leader combination. This outcome demonstrates the explanatory power of HTP µ-bioreactor data and the suitability of this platform as a screening tool in upstream development of microbial systems. Fast, reliable, and transferable screening data significantly reduce experiments in fully controlled bioreactor systems and accelerate process development at lower cost.


2014 ◽  
Vol 111 (12) ◽  
pp. 2486-2498 ◽  
Author(s):  
Georgina Espuny Garcia del Real ◽  
Jim Davies ◽  
Daniel G. Bracewell

Author(s):  
Kunjal Bharatkumar Mankad

Intelligent System (IS) can be defined as the system that incorporates intelligence into applications being handled by machines. The chapter extensively discusses the role of Genetic Algorithm (GA) in the search and optimization process along with discussing applications developed so far. A very detailed discussion on the Fuzzy Rule-Based System is presented along with major applications developed in different domains. The chapter presents algorithm of implementing intelligent procedure to decide whether a patient is prone to heart disease or not. The procedure evolves solutions using genetic operators and provides its decision automatically. The chapter presents discussion on the results achieved as a result of prototypical implementation of the evolutionary fuzzy hybrid model. The significant advantage of the presented research work is that applications that do not have any mathematical formulation and still demand optimization can be easily solved using the designed approach.


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