Difference between revisions of "Template:Heidelberg/improved part"
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}}: {{Heidelberg/highlbox|The ß-lactamase_E102F was the outstanding candidate of our deep learning software based mutation screen, which could <b>even grow at 19.2 mg/ml</b> without affection by the antibiotic. This results in a <b>improvement of at least 100 %</b> in comparison to the wildtype ß-lactamase. This remarkable gain of activity proves, that our software is not only able to recognize protein classes, but also to generate new function.}}|https://static.igem.org/mediawiki/2017/thumb/7/7c/T--Heidelberg--Team_Heidelberg_2017_ecoli_capacity_data.png/800px-T--Heidelberg--Team_Heidelberg_2017_ecoli_capacity_data.png}} | }}: {{Heidelberg/highlbox|The ß-lactamase_E102F was the outstanding candidate of our deep learning software based mutation screen, which could <b>even grow at 19.2 mg/ml</b> without affection by the antibiotic. This results in a <b>improvement of at least 100 %</b> in comparison to the wildtype ß-lactamase. This remarkable gain of activity proves, that our software is not only able to recognize protein classes, but also to generate new function.}}|https://static.igem.org/mediawiki/2017/thumb/7/7c/T--Heidelberg--Team_Heidelberg_2017_ecoli_capacity_data.png/800px-T--Heidelberg--Team_Heidelberg_2017_ecoli_capacity_data.png}} | ||
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Revision as of 16:57, 1 November 2017
Improved Part Introduction
ß-Lactamase_E102F
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The ß-lactamase_E102F was the outstanding candidate of our deep learning software based mutation screen, which could even grow at 19.2 mg/ml without affection by the antibiotic. This results in a improvement of at least 100 % in comparison to the wildtype ß-lactamase. This remarkable gain of activity proves, that our software is not only able to recognize protein classes, but also to generate new function.
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