Added more text and italicized multiline FAQs

about.py

@@ -107,6 +107,15 @@ FAQS = {
     "What do the datasets contain?": (
         "Both the GDPa1 and heldout test set contain the VH and VL sequences, as well as the full heavy chain sequence. The GDPa1 dataset is a mix of IgG1, IgG2, and IgG4 antibodies while the heldout test set only contains IgG1 antibodies. We also include the light chain subtype (lambda or kappa)."
     ),
+    # Made into a list so that we can italicize each line
+    "What units are used for the assays?": [
+        "The units, as reported in the [PROPHET-Ab preprint](https://www.biorxiv.org/content/10.1101/2025.05.01.651684v1) as well as the GDPa1 full excel datasheet, are as follows:",
+        "1. Titer: IgG titer assessed in clarified harvest supernatant reported in ug/mL",
+        "2. Tm2: Second transition peak for melting temperature determined using nanoDSF at a ramp rate of 1.5 degC/min reported in degC",
+        "3. HIC: Retention time on hydrophobic interaction reported in minutes",
+        "4. AC-SINS_pH7.4: Self association in a PBS pH 7.4 buffer reported as dLmax in nm",
+        "5. PR_CHO: Normalized polyreactivity score against CHO SMP",
+    ],
     "How were the heldout sequences designed?": (
         "We sampled 80 paired antibody sequences from [OAS](https://opig.stats.ox.ac.uk/webapps/oas/). We tried to represent the range of germline variants, sequence identities to germline, and CDR3 lengths. "
         "The sequences in the dataset are quite diverse as measured by pairwise sequence identity."
@@ -148,6 +157,9 @@ FAQS = {
     "How does the open-source prize work?": (
         "Participants who open-source their training code and methods will be eligible for the open-source prize (as well as the other prizes)."
     ),
+    "Can I use proprietary tools like AlphaFold3 for the open-source prize?": (
+        "Yes, using tools that have published their inference code under proprietary licenses is allowed (like AlphaFold3 and PROPERMAB), as long as code is available and fully reproducible."
+    ),
     "What do I need to submit?": (
         'There is a tab on the Hugging Face competition page to upload predictions for datasets - for each dataset participants need to submit a CSV containing a column for each property they would like to predict (e.g. called "HIC"), '
         "and a row with the sequence matching the sequence in the input file. These predictions are then evaluated in the backend using the Spearman rank correlation between predictions and experimental values, and these metrics are then added to the leaderboard. "

app.py

@@ -229,7 +229,13 @@ with gr.Blocks(theme=gr.themes.Default(text_size=sizes.text_lg)) as demo:
                 # Would love to make questions bold but accordion doesn't support it
                 question = f"{i+1}. {question}"
                 with gr.Accordion(question, open=False):
-                    gr.Markdown(f"*{answer}*")  # Italics for answers
+                    if isinstance(answer, list):
+                        # Italicize each line
+                        italicized_answer = "  \n".join(f"*{item}*" for item in answer)
+                        print(italicized_answer)
+                        gr.Markdown(italicized_answer)
+                    else:
+                        gr.Markdown(f"*{answer}*")  # Italics for answers
 
     # Footnote
     gr.Markdown(