Sparse graphical Gaussian modeling of the isoprenoid gene network in Arabidopsis thaliana

doi:10.1186/gb-2004-5-11-r92

Genome Biology

Volume 5
Issue 11

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Wille A
Zimmermann P
Vranová E
Fürholz A
Laule O
Bleuler S
Hennig L
Prelić A
von Rohr P
Thiele L
Zitzler E
Gruissem W
Bühlmann P

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Wille A
Zimmermann P
Vranová E
Fürholz A
Laule O
Bleuler S
Hennig L
Prelić A
von Rohr P
Thiele L
Zitzler E
Gruissem W
Bühlmann P
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Sparse graphical Gaussian modeling of the isoprenoid gene network in Arabidopsis thaliana

Anja Wille¹^,2^,3 , Philip Zimmermann¹^,4 , Eva Vranová¹^,4 , Andreas Fürholz¹^,4 , Oliver Laule¹^,4 , Stefan Bleuler¹^,5 , Lars Hennig¹^,4 , Amela Prelić¹^,5 , Peter von Rohr¹^,6 , Lothar Thiele¹^,5 , Eckart Zitzler¹^,5 , Wilhelm Gruissem¹^,4 and Peter Bühlmann¹^,3

¹Reverse Engineering Group, Swiss Federal Institute of Technology (ETH), Zurich

²Colab, ETH, Zurich 8092, Switzerland

³Seminar for Statistics, ETH, Zurich 8092, Switzerland

⁴Institute for Plant Sciences and Functional Genomics Center Zurich, ETH, Zurich 8092, Switzerland

⁵Computer Engineering and Networks Laboratory, ETH, Zurich 8092

⁶Institute of Computational Science, ETH, Zurich 8092, Switzerland

author email corresponding author email

Genome Biology 2004, 5:R92doi:10.1186/gb-2004-5-11-r92


Published:	25 October 2004

Subject areas: Plant biology, Genome studies, Genetics

Abstract

We present a novel graphical Gaussian modeling approach for reverse engineering of genetic regulatory networks with many genes and few observations. When applying our approach to infer a gene network for isoprenoid biosynthesis in Arabidopsis thaliana, we detect modules of closely connected genes and candidate genes for possible cross-talk between the isoprenoid pathways. Genes of downstream pathways also fit well into the network. We evaluate our approach in a simulation study and using the yeast galactose network.