| ABOUT_TEXT = """ | |
| ## About this challenge | |
| 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). | |
| **What is antibody developability?** | |
| Antibodies have to be manufacturable, stable in high concentrations, and have low off-target effects. | |
| Properties such as these can often hinder the progression of an antibody to the clinic, and are collectively referred to as 'developability'. | |
| 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. | |
| **How to submit?** | |
| TODO | |
| **How to evaluate?** | |
| TODO | |
| **How to contribute?** | |
| We'd like to add some more existing models to the leaderboard. Some examples of models we'd like to add: | |
| - TODO | |
| **FAQs** | |
| """ | |
| FAQS = { | |
| "Example FAQ with dropdown": """Full answer to this question""", | |
| } | |