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GReNaDIne: Data-Driven Approaches to Infer Gene Regulatory Networks in Python

Abstract : GReNaDIne (Gene Regulatory Network Data-driven Inference) is a Python package that implements 18 Machine Learning data-driven gene regulatory network inference methods. It includes 8 generalist pre-processing techniques, suitable for RNAseq and MicroArray datasets analysis, as well as 4 RNAseq normalization techniques. This package has been successfully assessed under the DREAM5 challenge benchmark dataset. The open source GReNaDIne Python package is freely available at https://gitlab.com/bf2i/grenadine as well as its latest documentation https://grenadine.readthedocs.io/en/latest/
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https://hal.archives-ouvertes.fr/hal-02863880
Contributor : Sergio Peignier <>
Submitted on : Wednesday, June 10, 2020 - 4:34:19 PM
Last modification on : Wednesday, July 8, 2020 - 12:42:18 PM

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Sergio Peignier, Pauline Schmitt, Federica Calevro. GReNaDIne: Data-Driven Approaches to Infer Gene Regulatory Networks in Python. 2020. ⟨hal-02863880⟩

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