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This article is part of the Research Topic Multifactorial disease: network disease

Mini Review ARTICLE

Front. Physiol., 23 July 2012 | http://dx.doi.org/10.3389/fphys.2012.00276

The power of Boolean implication networks

  • Institute of Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA

Human diseases have been investigated in the context of single genes as well as complex networks of genes. Though single gene approaches have been extremely successful in the past, most human diseases are complex and better characterized by multiple interacting genes commonly known as networks or pathways. With the advent of high-throughput technologies, a recent trend has been to apply network-based analysis to the huge amount of biological data. Analysis on Boolean implication network is one such technique that distinguishes itself based on its simplicity and robustness. Unlike traditional analyses, Boolean implication networks have the power to break into the mechanistic insights of human diseases. A Boolean implication network is a collection of simple Boolean relationships such as “if A is high then B is low.” So far, Boolean implication networks have been employed not only to discover novel markers of differentiation in both normal and cancer tissues, but also to develop robust treatment decisions for cancer patients. Therefore, analyses based on Boolean implication networks have potential to accelerate discoveries in human diseases, suggest therapeutics, and provide robust risk-adapted clinical strategies.

Keywords: bioinformatics, cancer, computational biology, differentiation, microarray analysis, prognostic biomarkers, stem cell, systems biology

Citation: Sahoo D (2012) The power of Boolean implication networks. Front. Physio. 3:276. doi: 10.3389/fphys.2012.00276

Received: 10 March 2012; Paper pending published: 04 April 2012;
Accepted: 27 June 2012; Published online: 23 July 2012.

Edited by:

Hans Westerhoff, University of Manchester, UK

Reviewed by:

Andrzej Michal Kierzek, University of Surrey, UK
Noriko Hiroi, Keio University, Japan
Kristina Gruden, National Institute of Biology, Slovenia

Copyright: © 2012 Sahoo. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

*Correspondence: Debashis Sahoo, Institute of Stem Cell Biology and Regenerative Medicine, Stanford University, 265 Campus Drive, Rm G3101B, Stanford, CA, USA. e-mail: sahoo@stanford.edu