Difference between revisions of "Team:Heidelberg/Software"

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     AiGEM|
 
     AiGEM|
 
     Artificial intelligence for Genetic Evolution Mimicking|
 
     Artificial intelligence for Genetic Evolution Mimicking|
     https://static.igem.org/mediawiki/2017/3/38/T--Heidelberg--2017_Background_Mountain.jpg|yellow|
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     https://static.igem.org/mediawiki/2017/3/38/T--Heidelberg--2017_GUS_PREPARATION_FRAGMENTS.svg|yellow|
  
     {{Heidelberg/abstract|https://static.igem.org/mediawiki/2017/3/35/T--Heidelberg--2017_GAIA_scoreVSmutation.png|
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     {{https://static.igem.org/mediawiki/2017/3/38/T--Heidelberg--2017_GUS_PREPARATION_FRAGMENTS.svg|
 
         abstract
 
         abstract
 
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                 To perform self-checks, and prevent misuse of directed evolution techniques, we developed SafetyNet a sensitive tool for the detection of harmful traits in sequences.|Explore
 
                 To perform self-checks, and prevent misuse of directed evolution techniques, we developed SafetyNet a sensitive tool for the detection of harmful traits in sequences.|Explore
 
                 }}
 
                 }}
                 {{Heidelberg/panelelement|Validation|https://static.igem.org/mediawiki/2017/2/2b/T--Heidelberg--2017_phage-titer-logo.png|https://2017.igem.org/Team:Heidelberg/Validation|
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                 {{Heidelberg/panelelement|Validation|https://static.igem.org/mediawiki/2017/3/38/T--Heidelberg--2017_GUS_PREPARATION_FRAGMENTS.svg|https://2017.igem.org/Team:Heidelberg/Validation|
 
                 Deploying GAIA, we fully <i>in silico</i> evolved a beta lactamase and reprogrammed the <i>E. Coli</i> beta glucuronidase towards beta galactosidase function.|Explore
 
                 Deploying GAIA, we fully <i>in silico</i> evolved a beta lactamase and reprogrammed the <i>E. Coli</i> beta glucuronidase towards beta galactosidase function.|Explore
 
                 }}
 
                 }}

Revision as of 12:19, 31 October 2017



AiGEM
Artificial intelligence for Genetic Evolution Mimicking
[[:Template:Https://static.igem.org/mediawiki/2017/3/38/T--Heidelberg--2017 GUS PREPARATION FRAGMENTS.svg]]
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DeeProtein

We apply deep learning models to harness the complex sequence to function relation in proteins.

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GAIA

By interfacing our trained models with a genetic algorithm we developed an in silico evolution tool.

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SafteyNet

To perform self-checks, and prevent misuse of directed evolution techniques, we developed SafetyNet a sensitive tool for the detection of harmful traits in sequences.

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Validation

Deploying GAIA, we fully in silico evolved a beta lactamase and reprogrammed the E. Coli beta glucuronidase towards beta galactosidase function.

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MAWS 2.0

Description