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Sep 12, 2024
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Aug 2, 2024 - DBTL-Data
Hägele, Lorena; Takors, Ralf, 2024, "Getting the right clones in an automated manner: an alternative to sophisticated colony-picking robotics", https://doi.org/10.18419/DARUS-4355, DaRUS, V1
In recent years, the Design-Build-Test-Learn (DBTL) cycle has become a key concept in strain engineering. Modern biofoundries enable automated DBTL cycling using robotic devices. However, both highly automated facilities and semi-automated facilities encounter bottlenecks in clone selection and screening. While fully automated biofoundries can take... |
Aug 2, 2024 -
Getting the right clones in an automated manner: an alternative to sophisticated colony-picking robotics
MS Excel Spreadsheet - 67.9 KB -
MD5: e79133871ed8ae10573b3f7e78f3995c
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Aug 2, 2024 -
Getting the right clones in an automated manner: an alternative to sophisticated colony-picking robotics
MS Excel Spreadsheet - 4.8 MB -
MD5: 14a90257f040871b6afb53e37ee34907
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Aug 2, 2024 -
Getting the right clones in an automated manner: an alternative to sophisticated colony-picking robotics
MS Excel Spreadsheet - 1.0 MB -
MD5: 7d1eb7d54f5e3bade1967740c4db164e
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Aug 2, 2024 -
Getting the right clones in an automated manner: an alternative to sophisticated colony-picking robotics
MS Excel Spreadsheet - 66.5 KB -
MD5: 35e8b8d496b79b85eb1402210233321c
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Aug 2, 2024 -
Getting the right clones in an automated manner: an alternative to sophisticated colony-picking robotics
MS Excel Spreadsheet - 2.0 MB -
MD5: 931b5fdda5170c9c175477daa2446e73
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Aug 2, 2024 -
Getting the right clones in an automated manner: an alternative to sophisticated colony-picking robotics
MS Excel Spreadsheet - 36.8 KB -
MD5: 32381d92c52d2035d1c9fe419f80a9c5
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Aug 2, 2024 -
Getting the right clones in an automated manner: an alternative to sophisticated colony-picking robotics
Python Source Code - 2.5 KB -
MD5: 68eb43da95135513a025eaa5c849ab9f
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Aug 2, 2024 -
Getting the right clones in an automated manner: an alternative to sophisticated colony-picking robotics
MS Excel Spreadsheet - 2.2 MB -
MD5: 94ac4e7c61b5645a2177074f79aeeb39
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