Commit
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11e5e48
1
Parent(s):
57878eb
Added some more info in About section
Browse files
app.py
CHANGED
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@@ -50,7 +50,7 @@ def get_leaderboard_object(assay: str | None = None):
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filter_columns = ["model"]
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if assay is None:
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filter_columns.append("property")
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# TODO how to sort filter columns?
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Leaderboard(
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value=df,
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datatype=["str", "str", "str", "number"],
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@@ -67,7 +67,11 @@ def show_output_box(message):
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#
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# def gradio_interface() -> gr.Blocks:
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with gr.Blocks() as demo:
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gr.Markdown("
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with gr.Tabs(elem_classes="tab-buttons"):
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with gr.TabItem("🚀 Leaderboard", elem_id="abdev-benchmark-tab-table"):
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gr.Markdown("# Antibody Developability Benchmark Leaderboard")
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@@ -85,8 +89,23 @@ with gr.Blocks() as demo:
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with gr.TabItem("❔About", elem_id="abdev-benchmark-tab-table"):
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gr.Markdown(
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"""
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## About
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-
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"""
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)
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filter_columns = ["model"]
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if assay is None:
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filter_columns.append("property")
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# TODO how to sort filter columns alphabetically?
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Leaderboard(
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value=df,
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datatype=["str", "str", "str", "number"],
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#
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# def gradio_interface() -> gr.Blocks:
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with gr.Blocks() as demo:
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gr.Markdown("""
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## Welcome to the Ginkgo Antibody Developability Benchmark Leaderboard!
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Participants can submit their model to the leaderboard by
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""")
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with gr.Tabs(elem_classes="tab-buttons"):
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with gr.TabItem("🚀 Leaderboard", elem_id="abdev-benchmark-tab-table"):
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gr.Markdown("# Antibody Developability Benchmark Leaderboard")
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with gr.TabItem("❔About", elem_id="abdev-benchmark-tab-table"):
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gr.Markdown(
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"""
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## About this challenge
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We're inviting the ML/bio community to predict developability properties for 244 antibodies from the [GDPa1 dataset](https://huggingface.co/datasets/ginkgo-datapoints/GDPa1).
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**What is antibody developability?**
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Antibodies have to be manufacturable, stable in high concentrations, and have low off-target effects.
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Properties such as these can often hinder the progression of an antibody to the clinic, and are collectively referred to as 'developability'.
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Here we show 5 of these properties and invite the community to submit and develop better predictors, which will be tested out on a heldout private set to assess model generalization.
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**How to submit?**
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TODO
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**How to evaluate?**
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TODO
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"""
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)
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