Reverse engineering gene regulatory networks with various machine learning methods: Analysis of microarray data

Marco Grzegorczyk; Dirk Husmeier; Adriano V. Werhli

doi:10.1002/9783527622818.ch5

Reverse engineering gene regulatory networks with various machine learning methods: Analysis of microarray data

Marco Grzegorczyk, Dirk Husmeier, Adriano V. Werhli

School of Biological Sciences

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

This chapter contains sections titled: * Introduction * Methods * The RAF Signalling Pathway * Criteria for Evaluating Learning Performances * Data * Simulations * Results * Discussion * Conclusion * References

Original language	English
Title of host publication	Analysis of Microarray Data
Subtitle of host publication	A Network-Based Approach
Publisher	Wiley-VCH Verlag GmbH & Co. KGaA
Chapter	5
Pages	101-142
Number of pages	42
ISBN (Print)	9783527622818
DOIs	https://doi.org/10.1002/9783527622818.ch5
Publication status	Published - 13 Feb 2008

Keywords

DNA microarrays
analysis
systems biology
gene regulatory networks
relevance networks
graphical Gaussian models
Bayesian networks
Bayesian inference
Markov chain Monte Carlo
cytometry data
raf signaling pathway
machine learning methods

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10.1002/9783527622818.ch5

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1 Finished

SynthSys; formerly CSBE: Centre for Systems Biology at Edinburgh
Millar, A., Beggs, J., Ghazal, P., Goryanin, I., Hillston, J., Plotkin, G., Tollervey, D., Walton, A. & Robertson, K.
BBSRC
8/01/07 → 31/12/12
Project: Research

Cite this

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title = "Reverse engineering gene regulatory networks with various machine learning methods: Analysis of microarray data",

abstract = "This chapter contains sections titled: * Introduction * Methods * The RAF Signalling Pathway * Criteria for Evaluating Learning Performances * Data * Simulations * Results * Discussion * Conclusion * References",

keywords = "DNA microarrays, analysis, systems biology, gene regulatory networks, relevance networks, graphical Gaussian models, Bayesian networks, Bayesian inference, Markov chain Monte Carlo, cytometry data, raf signaling pathway, machine learning methods",

author = "Marco Grzegorczyk and Dirk Husmeier and Werhli, {Adriano V.}",

year = "2008",

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doi = "10.1002/9783527622818.ch5",

language = "English",

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T2 - Analysis of microarray data

AU - Grzegorczyk, Marco

AU - Husmeier, Dirk

AU - Werhli, Adriano V.

PY - 2008/2/13

Y1 - 2008/2/13

N2 - This chapter contains sections titled: * Introduction * Methods * The RAF Signalling Pathway * Criteria for Evaluating Learning Performances * Data * Simulations * Results * Discussion * Conclusion * References

AB - This chapter contains sections titled: * Introduction * Methods * The RAF Signalling Pathway * Criteria for Evaluating Learning Performances * Data * Simulations * Results * Discussion * Conclusion * References

KW - DNA microarrays

KW - analysis

KW - systems biology

KW - gene regulatory networks

KW - relevance networks

KW - graphical Gaussian models

KW - Bayesian networks

KW - Bayesian inference

KW - Markov chain Monte Carlo

KW - cytometry data

KW - raf signaling pathway

KW - machine learning methods

U2 - 10.1002/9783527622818.ch5

DO - 10.1002/9783527622818.ch5

M3 - Chapter

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SP - 101

EP - 142

BT - Analysis of Microarray Data

PB - Wiley-VCH Verlag GmbH & Co. KGaA

ER -

Reverse engineering gene regulatory networks with various machine learning methods: Analysis of microarray data

Abstract

Keywords

Access to Document

SynthSys; formerly CSBE: Centre for Systems Biology at Edinburgh

Cite this