A Bayesian data fusion based approach for learning genome-wide transcriptional regulatory networks

  • Elisabetta Sauta (Creator)
  • A. Demartini (Creator)
  • Francesca Vitali (Creator)
  • Alberto Riva (Creator)
  • Riccardo Bellazzi (Creator)
  • Riccardo Bellazzi (Creator)

Dataset

Description

Abstract Background Reverse engineering of transcriptional regulatory networks (TRN) from genomics data has always represented a computational challenge in System Biology. The major issue is modeling the complex crosstalk among transcription factors (TF...
Date made available2020
Publisherfigshare

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