| Autor: |
Geisen, Reinhild, Davara, Jaydip, Sebens, Susanne, Kollenda, Sebastian, Werdelmann, Ben |
| Zdroj: |
BioSpektrum; Oct2023, Vol. 29 Issue 6, p646-648, 3p |
| Abstrakt: |
Traditional methods for confirming the monoclonality of cell lines are time-consuming, subjective, limited in scalability, and susceptible to false positives. We have developed a novel approach that can detect individual cells with over 99 percent accuracy just a few hours after seeding by employing artificial intelligence. This advancement significantly reduces the time required for analysis, improves throughput, and provides a more efficient selection process for researchers. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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