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Unsupervised GRN Ensemble

Author
Bellot, P.; Salembier, P.; Pham, N C.; Meyer, P. E.
Type of activity
Book chapter
Book
Gene regulatory networks: methods and protocols
First page
283
Last page
302
Publisher
Springer
Date of publication
2019
ISBN
978-1-4939-8881-5
DOI
10.1007/978-1-4939-8882-2
Repository
http://hdl.handle.net/2117/176898 Open in new window
URL
https://link.springer.com/book/10.1007/978-1-4939-8882-2 Open in new window
Abstract
Inferring gene regulatory networks from expression data is a very challenging problem that has raised the interest of the scientific community. Different algorithms have been proposed to try to solve this issue, but it has been shown that different methods have some particular biases and strengths, and none of them is the best across all types of data and datasets. As a result, the idea of aggregating various network inferences through a consensus mechanism naturally arises. In this chapter, a c...
Citation
Bellot, P. [et al.]. Unsupervised GRN Ensemble. A: "Gene regulatory networks: methods and protocols". Berlín: Springer, 2019, p. 283-302.
Keywords
Consensus network algorithms, Gene expression data, Gene regulatory networks, Meta-analysis
Group of research
GPI - Image and Video Processing Group
Universitat Politècnica de Catalunya

Participants