Update app.py

app.py

@@ -229,20 +229,26 @@ def gradio_inference(dna_sequence, run_mapping):
 # --- THE UI LAYOUT ---
 with gr.Blocks(theme=gr.themes.Soft(), title="🧬 The Genomic Oracle 🧬") as demo:
     gr.Markdown(
+gr.Markdown(
         """
-        # 🧬 The Genomic Oracle 🧬
-        **University of Maryland Global Campus (UMGC) | Bioinformatics Capstone Project**
+        <div style="text-align: center;">
+            <h1 style="font-size: 3.5rem; font-weight: bold; margin-bottom: 0.2rem;">🧬 The Genomic Oracle 🧬</h1>
+            <h3 style="margin-top: 0; font-weight: normal;"><b>University of Maryland Global Campus (UMGC)</b> | Bioinformatics Capstone Project</h3>
+        </div>
+        
+        <hr>
         
         Welcome to the official interface for **The Genomic Oracle**, a cascaded machine learning pipeline designed for high-precision DNA sequence classification. 
         
         ### 🧠 The 4-Stage Architecture
-        1. **The Gatekeeper:** Logistic Regression Model rapidly screens raw k-mer vectors to identify protein-coding vs. non-coding potential.
-        2. **Structural Mapper:** LightGBM Model classifies the sequence into 1 of 7 structural features (e.g., Exons, UTRs, Enhancers).
-        3. **Phenotype Prediction:** Sequences flagged as Coding are passed through a custom ALiBi BERT transformer to predict specific traits.
-        4. **Regulatory Validation:** Sequences flagged as Non-Coding Promoters are routed to a DNABERT-2 spatial attention neural network.
+        1. **The Gatekeeper:** Logistic Regression model rapidly screens raw k-mer vectors to identify protein-coding vs. non-coding potential.
+        2. **Structural Mapper:** LightGBM model classifies the sequence into 1 of 7 structural features (e.g., Exons, UTRs, Enhancers).
+        3. **Phenotype Prediction:** Sequences flagged as Coding are passed through a custom ALiBi BERT transformer to predict specific phenotypes.
+        4. **Regulatory Validation:** Sequences flagged as Non-Coding Promoters are validated by a DNABERT-2 spatial attention neural network.
         ---
         """
     )
+    )
     
     with gr.Row():
         with gr.Column(scale=1):