Abstract
Various techniques for gene network inference learn from different types of data, have different theoretical approaches, and use different types of statistics. For example, an algorithm using a Bayesian approach may be extracting different information from the data than one using a regression approach. The idea behind the consensus step is to combine the inferential abilities of different methods to arrive at a consensus network. There are many different ways to combine the inferred networks.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2012 The Author(s)
About this chapter
Cite this chapter
Lingeman, J.M., Shasha, D. (2012). Pipelines. In: Network Inference in Molecular Biology. SpringerBriefs in Electrical and Computer Engineering. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3113-8_5
Download citation
DOI: https://doi.org/10.1007/978-1-4614-3113-8_5
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-3112-1
Online ISBN: 978-1-4614-3113-8
eBook Packages: EngineeringEngineering (R0)