PNNL-CompBio/coderdata
Dataset package for facile training and testing of machine learning/AI algorithms that predict drug response in cancer model systems.
This project provides a standardized collection of cancer-related molecular and drug sensitivity data. It takes raw omics data and drug response measurements, processes them, and outputs harmonized datasets. Cancer researchers and computational biologists can use this to develop and test machine learning models for predicting how cancer cells will respond to different drug treatments.
Available on PyPI.
Use this if you need a reliable, pre-processed benchmark dataset to train and validate machine learning algorithms that predict drug outcomes in cancer models.
Not ideal if you are looking for raw, uncurated data or if your research is outside the domain of cancer drug response prediction.
Stars
20
Forks
4
Language
Jupyter Notebook
License
BSD-2-Clause
Category
Last pushed
Feb 11, 2026
Commits (30d)
0
Dependencies
5
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/PNNL-CompBio/coderdata"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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