An open API service providing mapping between scientific papers and software projects that are mentioned in them.

Papers: 10.1186/s12859-020-3510-1

https://doi.org/10.1186/s12859-020-3510-1

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

Cited by: 3
Author(s): Elisabetta Sauta, Andrea Demartini, Francesca Vitali, Alberto Riva, Riccardo Bellazzi
Published: about 5 years ago

Software Mentions 3

cran: bnlearn
Bayesian Network Structure Learning, Parameter Learning and Inference
Papers that mentioned: 113
Very Likely Science (85)
pypi: bnlearn
Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.
Papers that mentioned: 113
Very Likely Science (90)
pypi: MACS2
Model Based Analysis for ChIP-Seq data
Papers that mentioned: 1,203
Very Likely Science (100)