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Erva Ulusoy
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4cc17e2
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Parent(s):
ba68f00
Update Domain2GO.py
Browse files- Domain2GO.py +9 -20
Domain2GO.py
CHANGED
@@ -15,7 +15,6 @@ def convert_df(df):
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with st.sidebar:
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st.title("Domain2GO: Mutual Annotation-Based Prediction of Protein Domain Functions")
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st.write("[![biorxiv](https://img.shields.io/badge/bioRxiv-2022.11.03.514980-b31b1b.svg)](https://www.biorxiv.org/content/10.1101/2022.11.03.514980v1) [![github-repository](https://img.shields.io/badge/GitHub-black?logo=github)](https://github.com/HUBioDataLab/Domain2GO)")
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@@ -62,16 +61,15 @@ with st.sidebar:
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st.warning('Please enter your email and protein sequence first. If you have already entered your email and protein sequence, please check that your email is valid.')
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with st.sidebar:
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st.
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if not submitted:
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# on main page, write warning message if user has not submitted email and sequence
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st.markdown("""
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@@ -137,13 +135,4 @@ else:
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mime="text/csv",
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)
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# # <div style="background-color:#f0f2f6;padding:10px">
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# st.markdown("""
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# <div style="position: relative;background-color: #f0f2f6;padding:10px;">
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# <div style="position: absolute; bottom: 5px;">
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# <p style="color:#b22d2a;font-size:15px;">Disclaimer</p>
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# <p style="color:#000000;font-size:14px;">This program is designed to generate predictions for a single protein due to the extended runtime of InterProScan. If you need predictions for multiple UniProtKB/Swiss-Prot proteins, we recommend utilizing our comprehensive protein function prediction dataset available in our <a href="https://github.com/HUBioDataLab/Domain2GO">Github repository</a>.</p>
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# </div>
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# </div>
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# """, unsafe_allow_html=True)
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with st.sidebar:
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st.title("Domain2GO: Mutual Annotation-Based Prediction of Protein Domain Functions")
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st.write("[![biorxiv](https://img.shields.io/badge/bioRxiv-2022.11.03.514980-b31b1b.svg)](https://www.biorxiv.org/content/10.1101/2022.11.03.514980v1) [![github-repository](https://img.shields.io/badge/GitHub-black?logo=github)](https://github.com/HUBioDataLab/Domain2GO)")
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st.warning('Please enter your email and protein sequence first. If you have already entered your email and protein sequence, please check that your email is valid.')
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with st.sidebar:
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c = st.container()
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c.markdown("---")
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c.markdown(
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"""
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<div style="padding:5px">
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<p style="color:#000000;font-size:12px;">Disclaimer: This program is designed to generate predictions for a single protein due to the extended runtime of InterProScan. If you need predictions for multiple UniProtKB/Swiss-Prot proteins, we recommend utilizing our comprehensive protein function prediction dataset available in our <a href="https://github.com/HUBioDataLab/Domain2GO">Github repository</a>.</p>
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</div>
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""", unsafe_allow_html=True)
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if not submitted:
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# on main page, write warning message if user has not submitted email and sequence
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st.markdown("""
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mime="text/csv",
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)
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