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@@ -6,7 +6,7 @@ base_model: westlake-repl/SaProt_35M_AF2
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  <!-- Provide a quick summary of what the model is/does. -->
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  This model is trained on a sigle site deep mutation scanning dataset and
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- can be used to predict fitness score of protein GAL4_YEAST (Regulatory protein).
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  ## Protein Function
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  This protein is a positive regulator for the gene expression of the galactose-induced genes such as GAL1, GAL2, GAL7, GAL10, and MEL1 which code for the enzymes used to convert galactose to glucose.
@@ -16,6 +16,9 @@ It recognizes a 17 base pair sequence in (5'-CGGRNNRCYNYNCNCCG-3') the upstream
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  protein level regression
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  ### Dataset description
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  The dataset is from [Deep generative models of genetic variation capture the effects of mutations](https://www.nature.com/articles/s41592-018-0138-4).
 
 
 
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  ### Model input type
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  Amino acid sequence
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  ### Performance
 
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  <!-- Provide a quick summary of what the model is/does. -->
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  This model is trained on a sigle site deep mutation scanning dataset and
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+ can be used to predict fitness score of mutant amino acid sequence of protein [GAL4_YEAST](https://www.uniprot.org/uniprotkb/P04386/entry) (Regulatory protein).
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  ## Protein Function
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  This protein is a positive regulator for the gene expression of the galactose-induced genes such as GAL1, GAL2, GAL7, GAL10, and MEL1 which code for the enzymes used to convert galactose to glucose.
 
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  protein level regression
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  ### Dataset description
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  The dataset is from [Deep generative models of genetic variation capture the effects of mutations](https://www.nature.com/articles/s41592-018-0138-4).
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+ And can also be found on [SaprotHub dataset](https://huggingface.co/datasets/SaProtHub/DMS_GAL4_YEAST).
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+ Label means fitness score of each mutant amino acid sequence.
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  ### Model input type
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  Amino acid sequence
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  ### Performance