AmelieSchreiber
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README.md
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@@ -34,7 +34,7 @@ there are three protein sequence examples. The first is a DNA binding protein tr
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([see UniProt entry here](https://www.uniprot.org/uniprotkb/D3ZG52/entry)).
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The second and third were obtained using [EvoProtGrad](https://github.com/Amelie-Schreiber/sampling_protein_language_models/blob/main/EvoProtGrad_copy.ipynb)
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a Markov Chain Monte Carlo method of (in silico) directed evolution of proteins based on a form of Gibbs sampling. The mutatant-type
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protein sequences in theory should have similar binding sites to the wild-type protein sequence, but perhaps with higher binding affinity.
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Testing this out on the model, we see the two proteins indeed have the same binding sites, which validates to some degree that the model
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has learned to predict binding sites well (and that EvoProtGrad works as intended).
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([see UniProt entry here](https://www.uniprot.org/uniprotkb/D3ZG52/entry)).
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The second and third were obtained using [EvoProtGrad](https://github.com/Amelie-Schreiber/sampling_protein_language_models/blob/main/EvoProtGrad_copy.ipynb)
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a Markov Chain Monte Carlo method of (*in silico*) directed evolution of proteins based on a form of Gibbs sampling. The mutatant-type
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38 |
protein sequences in theory should have similar binding sites to the wild-type protein sequence, but perhaps with higher binding affinity.
|
39 |
Testing this out on the model, we see the two proteins indeed have the same binding sites, which validates to some degree that the model
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40 |
has learned to predict binding sites well (and that EvoProtGrad works as intended).
|