Spaces:
Running
on
Zero
Running
on
Zero
Add Model Descriptions again
Browse files
app.py
CHANGED
@@ -57,10 +57,37 @@ def classify(sequence):
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pred = predict_ensemble(protT5_emb, concat, model_protT5, model_cat)
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return "Potential Allergen" if pred.item() == 1 else "Non-Allergen"
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demo = gr.Interface(fn=classify,
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inputs=gr.Textbox(lines=3, placeholder="Enter protein sequence..."),
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outputs=gr.Label(label="Prediction")
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if __name__ == "__main__":
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demo.launch()
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pred = predict_ensemble(protT5_emb, concat, model_protT5, model_cat)
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return "Potential Allergen" if pred.item() == 1 else "Non-Allergen"
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description_md = """
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### 📌 **About AllerTrans – An Allergenicity Prediction Tool for Protein Sequences**
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**🧬 Input Format – FASTA Sequences**
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This tool accepts protein sequences in FASTA format
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**🧾 Output Explanation**
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AllerTrans classifies your input sequence into one of the following categories:
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🟢 Non-Allergen:
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The protein is unlikely to cause an allergic reaction and can be considered safe in terms of allergenicity.
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🔴 Potential Allergen:
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The protein has the potential to trigger an allergic response or exhibit cross-reactivity in certain individuals. While not all individuals may experience reactions, these proteins cannot be considered safe.
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**💡 Accepted Proteins**
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- Natural and also recombinant proteins
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🔎 **Note of Caution**:
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While our model demonstrates promising performance—particularly with recombinant proteins, as evidenced by our additional evaluation with a recombinant protein dataset
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from UniProt—**we advise caution when generalizing the results to all constructs and modifications of recombinant protein**. The generizability of the model to various recombinant scenarios has not been fully explored.
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**⚠️ Disclaimer**
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Although AllerTrans provides highly accurate predictions, it is intended as a screening tool. For clinical or regulatory decisions, always confirm results with experimental validation.
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"""
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demo = gr.Interface(fn=classify,
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inputs=gr.Textbox(lines=3, placeholder="Enter protein sequence..."),
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outputs=gr.Label(label="Prediction"),
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description=description_md))
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if __name__ == "__main__":
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demo.launch()
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