Inferring cellular networks – a review

doi:10.1186/1471-2105-8-S6-S5

BMC Bioinformatics
Volume 8
Suppl 6

Viewing options:

Abstract
Full text
PDF (502KB)

Associated material:

PubMed record

Related literature:

Articles citing this article
on BioMed Central
on Google Scholar
on ISI Web of Science
on PubMed Central
Other articles by authors
on Google Scholar

Markowetz F
Spang R

on PubMed

Markowetz F
Spang R
Related articles/pages
on Google

on Google Scholar

on PubMed

Tools:

Post to:

This article is part of the supplement: Otto Warburg International Summer School and Workshop on Networks and Regulation .

Review

Inferring cellular networks – a review

Florian Markowetz¹^,2 and Rainer Spang¹^,3

¹Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany

²Princeton University, Lewis-Sigler Institute for Integrative Genomics and Dept. of Computer Science, Princeton, NJ 08544, USA

³Present affiliation: University Regensburg, Institute of Functional Genomics, Josef-Engert-Str. 9, 93053 Regensburg, Germany

author email corresponding author email

BMC Bioinformatics 2007, 8(Suppl 6):S5doi:10.1186/1471-2105-8-S6-S5


Published:	27 September 2007

Abstract

In this review we give an overview of computational and statistical methods to reconstruct cellular networks. Although this area of research is vast and fast developing, we show that most currently used methods can be organized by a few key concepts. The first part of the review deals with conditional independence models including Gaussian graphical models and Bayesian networks. The second part discusses probabilistic and graph-based methods for data from experimental interventions and perturbations.