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Team ZJU-China 2024 Software Tool

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Understanding the laws that govern a phenomenon is the core of scientific progress. This is especially true when the goal is to model the interplay between different aspects in a causal fashion.

Description

ExpAscribe: a causal inference framework for quantitative experiment ascription and its derivative process, with python library and portable webapp provided by Team ZJU-China 2024.

Features

  • Quantitative ascription-validation-intervention-optimization closed loop, equipped with state-of-the-art ML studies
  • Validated by experimental work
  • Compatible with existing database formats, i.e. GEO and ArrayExpress
  • Detailed documentation, example notebooks and tutorial videos

For more information, please visit our Wiki and Pypi Repo