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

Sergio Peignier (1) , Pauline Schmitt (1) , Federica Calevro (1)

1 BF2I - Biologie Fonctionnelle, Insectes et Interactions

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/

Mots clés: Python package; Machine Learning; GRN Inference; Gene Regulatory Networks

Domaines: Intelligence artificielle [cs.AI]; Bio-informatique [q-bio.QM]

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