Dataset research report
Proteinmpnn research report
A reproducible data report with schema notes, generated chart evidence, suggested follow-up questions, and export-ready Helix queries.
Executive Summary
Curated ProteinMPNN training dataset The multi-chain training data for ProteinMPNN Quickstart Usage Install HuggingFace Datasets package Each subset can be loaded into python using the Huggingface datasets library. First, from the command line install the datasets library $ pip install datasets Optionally set the cache directory, e.g. $ HF_HOME=${HOME}/.cache/huggingface/ $ export HF_HOME then, from within python load the datasets library >>> import datasets… See the full description on the dataset page: https://huggingface.co/datasets/RosettaCommons/ProteinMPNN.
Follow-Up Queries
Method And Limits
- Load the catalog entry and preview rows from the processed dataset file.
- Infer numeric, categorical, time, and location fields from real columns.
- Generate a small set of defensive Plotly chart specifications from that profile.
- Expose each chart idea as a query link so the report can be rerun or exported in Helix.
This report is intentionally reproducible. It uses the local catalog metadata and generated chart specifications rather than claiming external conclusions beyond the dataset.