Abstract
The objective of the project reported in the present chapter was the reverse engineering of gene regulatory networks related to quorum sensing in the plant pathogen Pectobacterium atrosepticum from micorarray gene expression profiles, obtained from the wild-type and eight knockout strains. To this end, we have applied various recent methods from multivariate statistics and machine learning: graphical Gaussian models, sparse Bayesian regression, LASSO (least absolute shrinkage and selection operator), Bayesian networks, and nested effects models. We have investigated the degree of similarity between the predictions obtained with the different approaches, and we have assessed the consistency of the reconstructed networks in terms of global topological network properties, based on the node degree distribution. The chapter concludes with a biological evaluation of the predicted network structures.
| Language | English |
|---|---|
| Title of host publication | Computational Biology |
| Editors | David Fenyö |
| Place of Publication | New York |
| Publisher | Springer |
| Chapter | 17 |
| Pages | 253-281 |
| Number of pages | 29 |
| ISBN (Print) | 9781607618416, 9781607618423 |
| DOIs | |
| Publication status | Published - 23 Sep 2010 |
Publication series
| Name | Methods in Molecular Biology |
|---|---|
| Publisher | Springer Verlag |
| Volume | 673 |
| ISSN (Print) | 1064-3745 |
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Keywords
- Pectobacterium atrosepticum
- quorum sensing
- transposon mutagenesis
- microarrays
- graphical Gaussian models
- sparse Bayesian regression
- Bayesian networks
- nested effects models
- gene ontologies
Cite this
}
Reverse engineering gene regulatory networks related to quorum sensing in the plant pathogen Pectobacterium atrosepticum. / Lin, Kuang; Husmeier, Dirk; Dondelinger, Frank; Mayer, Claus D.; Liu, Hui; Pritchard, Leighton; Salmond, George P. C.; Toth, Ian K.; Birch, Paul R. J.
Computational Biology. ed. / David Fenyö. New York : Springer, 2010. p. 253-281 (Methods in Molecular Biology; Vol. 673).Research output: Chapter in Book/Report/Conference proceeding › Chapter
TY - CHAP
T1 - Reverse engineering gene regulatory networks related to quorum sensing in the plant pathogen Pectobacterium atrosepticum
AU - Lin, Kuang
AU - Husmeier, Dirk
AU - Dondelinger, Frank
AU - Mayer, Claus D.
AU - Liu, Hui
AU - Pritchard, Leighton
AU - Salmond, George P. C.
AU - Toth, Ian K.
AU - Birch, Paul R. J.
PY - 2010/9/23
Y1 - 2010/9/23
N2 - The objective of the project reported in the present chapter was the reverse engineering of gene regulatory networks related to quorum sensing in the plant pathogen Pectobacterium atrosepticum from micorarray gene expression profiles, obtained from the wild-type and eight knockout strains. To this end, we have applied various recent methods from multivariate statistics and machine learning: graphical Gaussian models, sparse Bayesian regression, LASSO (least absolute shrinkage and selection operator), Bayesian networks, and nested effects models. We have investigated the degree of similarity between the predictions obtained with the different approaches, and we have assessed the consistency of the reconstructed networks in terms of global topological network properties, based on the node degree distribution. The chapter concludes with a biological evaluation of the predicted network structures.
AB - The objective of the project reported in the present chapter was the reverse engineering of gene regulatory networks related to quorum sensing in the plant pathogen Pectobacterium atrosepticum from micorarray gene expression profiles, obtained from the wild-type and eight knockout strains. To this end, we have applied various recent methods from multivariate statistics and machine learning: graphical Gaussian models, sparse Bayesian regression, LASSO (least absolute shrinkage and selection operator), Bayesian networks, and nested effects models. We have investigated the degree of similarity between the predictions obtained with the different approaches, and we have assessed the consistency of the reconstructed networks in terms of global topological network properties, based on the node degree distribution. The chapter concludes with a biological evaluation of the predicted network structures.
KW - Pectobacterium atrosepticum
KW - quorum sensing
KW - transposon mutagenesis
KW - microarrays
KW - graphical Gaussian models
KW - sparse Bayesian regression
KW - Bayesian networks
KW - nested effects models
KW - gene ontologies
UR - http://www.scopus.com/inward/record.url?scp=79952111742&partnerID=8YFLogxK
U2 - 10.1007/978-1-60761-842-3_17
DO - 10.1007/978-1-60761-842-3_17
M3 - Chapter
SN - 9781607618416
SN - 9781607618423
T3 - Methods in Molecular Biology
SP - 253
EP - 281
BT - Computational Biology
A2 - Fenyö, David
PB - Springer
CY - New York
ER -