From 5e16268c5ab3e94ea77704420a0a8bd87e671ecf Mon Sep 17 00:00:00 2001
From: Navan Chauhan <navanchauhan@gmail.com>
Date: Sun, 8 Nov 2020 17:22:01 +0530
Subject: [PATCH] removed description from about and added linkk to Qrious

---
 app/templates/about.html | 1 -
 app/templates/home.html  | 4 ++--
 2 files changed, 2 insertions(+), 3 deletions(-)

diff --git a/app/templates/about.html b/app/templates/about.html
index 59fdcd4..4e4c710 100644
--- a/app/templates/about.html
+++ b/app/templates/about.html
@@ -2,7 +2,6 @@
 {% set active_page = "about" %}
 {% block main %}
     <h1>About Curie Web</h1>
-    <p>Curie Web is a web interface for my private Python Library called "Curie", with some aditional superpowers.</p>
     <h4>Docking</h4>
     <p>This section deals with Molecular Docking and protein-ligand interactions. It uses AutoDock Vina<sup>[1]</sup> for docking, PyMOL<sup>[2]</sup> for visualisations, and PLIP<sup>[3]</sup> for interactions and binding site detection.</p>
     <h4>Drug Designing</h4>
diff --git a/app/templates/home.html b/app/templates/home.html
index d67cac7..f4d1a99 100644
--- a/app/templates/home.html
+++ b/app/templates/home.html
@@ -20,10 +20,10 @@
     <ul>
         <li><a href="{{ url_for('pubmed') }}">PubMed Search</a> - Handy PubMed search with direct download links</li>
         <li><a href="{{url_for('pubchem')}}">PubChem Search</a> - Get Compound SMILES</li>
-        <li>Qrious App - You can enter a question for a set of papers (e.g. ChemRxiv preprints) and it uses AI to answer it for each individual paper based on their abstract</li>
+        <li><a href="https://github.com/navanchauhan/Qrious">Qrious App</a> (v0.1) - You can enter a question for a set of papers (e.g. ChemRxiv preprints) and it uses AI to answer it for each individual paper based on their abstract</li>
     </ul>
 
-    <h3>Analyse</h3>
+    <h3>Analyse (Beta)</h3>
     <ul>
         <li><a href="{{ url_for('propalert') }}">Chemical Properties and Alerts</a> - Find Chemical properties and check structure for alerts.</li>
         <li><a href="#">Druggability</a> - Classify druggability of a compound using a ML Model.</li>