import streamlit as st import pandas as pd title_app = "ReVa" title_app2 = "ReVa:AI For Design Vaccine In Silico" description = """ReVa is an AI-based software for predicting linear epitopes, allergenicity, antigenicity, toxicity, and conducting physicochemical calculations. It also performs docking (force field calculations and machine learning based) with human receptors and several simulations for adjuvant addition.""" button1_color = "#018205" nav_color = "#018205" jumbotron_color = "#73ff77" body_color = "#b7f7b9" # Updated body background color # Mengubah title dan icon web dengan gambar st.set_page_config( page_title=title_app, page_icon="asset/img/kaede_kayano.ico" ) st.markdown( """ """, unsafe_allow_html=True ) # Custom CSS for styling custom_css = f""" """ # Inject custom CSS st.markdown(custom_css, unsafe_allow_html=True) # Navbar st.markdown( f""" """ , unsafe_allow_html=True) # Jumbotron st.markdown( f"""

{title_app2}

{description}

""" , unsafe_allow_html=True) # Table st.write("## Features") st.markdown( f"""
  1. B Cell Or T Cell Linear Epitope Prediction
  2. Allergenicity Prediction
  3. Antigenicity Prediction
  4. Toxicitty Prediction
  5. BLAST Result Epitope
  6. Phsycochemical Calculator
  7. Scoring Using Force Field
  8. Scoring Using Machine Learning(Regression Based)
  9. Van Der Walls Calculator
  10. Adjuvant Addition Simulation And Scoring Using Force Field
  11. Adjuvant Addition Simulation And Scoring Using Machine Learning
""" , unsafe_allow_html=True) # Contact st.write("## Contact") st.markdown( f""" """ , unsafe_allow_html=True) # Footer st.markdown( f""" """ , unsafe_allow_html=True) footer = st.markdown( f""" """ , unsafe_allow_html=True)