Modelling of macrophage gene expression in the interferon pathway

L. Yu; S. Marshall; T. Forster; P. Ghazal

doi:10.1109/GENSIPS.2006.353148

Modelling of macrophage gene expression in the interferon pathway

L. Yu, S. Marshall, T. Forster, P. Ghazal

Electronic And Electrical Engineering

Research output: Contribution to conference › Paper

6 Citations (Scopus)

Abstract

We propose a modeling approach based on Probabilistic Boolean Networks for the inference of genetic regulatory networks from gene expression time-course data in different biological conditions i.e. making use of the information contained in sets of genes and the interaction between genes rather than single-gene analyses. This model is a collection of traditional Probabilistic Boolean Networks. We also present an approach which is based on constrained prediction and Coefficient of Determination (COD) for the identification of the model from gene expression data. The modeling approach is applied in the context of pathway biology to the analysis of gene interaction networks.

Original language	English
Pages	45-46
Number of pages	2
DOIs	https://doi.org/10.1109/GENSIPS.2006.353148
Publication status	Published - 30 May 2007
Event	2006 IEEE International Workshop on Genomic Signal Processing and Statstics - Texas, United States Duration: 28 May 2006 → 30 May 2006

Conference

Conference	2006 IEEE International Workshop on Genomic Signal Processing and Statstics
Abbreviated title	GENSIPS 2006
Country/Territory	United States
City	Texas
Period	28/05/06 → 30/05/06

Keywords

bioinformatics
biological system modeling
computational biology
gene expression
informatics
predictive models
macrophage
modelling
interferon pathway

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10.1109/GENSIPS.2006.353148

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abstract = "We propose a modeling approach based on Probabilistic Boolean Networks for the inference of genetic regulatory networks from gene expression time-course data in different biological conditions i.e. making use of the information contained in sets of genes and the interaction between genes rather than single-gene analyses. This model is a collection of traditional Probabilistic Boolean Networks. We also present an approach which is based on constrained prediction and Coefficient of Determination (COD) for the identification of the model from gene expression data. The modeling approach is applied in the context of pathway biology to the analysis of gene interaction networks.",

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author = "L. Yu and S. Marshall and T. Forster and P. Ghazal",

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doi = "10.1109/GENSIPS.2006.353148",

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T1 - Modelling of macrophage gene expression in the interferon pathway

AU - Yu, L.

AU - Marshall, S.

AU - Forster, T.

AU - Ghazal, P.

PY - 2007/5/30

Y1 - 2007/5/30

N2 - We propose a modeling approach based on Probabilistic Boolean Networks for the inference of genetic regulatory networks from gene expression time-course data in different biological conditions i.e. making use of the information contained in sets of genes and the interaction between genes rather than single-gene analyses. This model is a collection of traditional Probabilistic Boolean Networks. We also present an approach which is based on constrained prediction and Coefficient of Determination (COD) for the identification of the model from gene expression data. The modeling approach is applied in the context of pathway biology to the analysis of gene interaction networks.

AB - We propose a modeling approach based on Probabilistic Boolean Networks for the inference of genetic regulatory networks from gene expression time-course data in different biological conditions i.e. making use of the information contained in sets of genes and the interaction between genes rather than single-gene analyses. This model is a collection of traditional Probabilistic Boolean Networks. We also present an approach which is based on constrained prediction and Coefficient of Determination (COD) for the identification of the model from gene expression data. The modeling approach is applied in the context of pathway biology to the analysis of gene interaction networks.

KW - bioinformatics

KW - biological system modeling

KW - computational biology

KW - gene expression

KW - informatics

KW - predictive models

KW - macrophage

KW - modelling

KW - interferon pathway

U2 - 10.1109/GENSIPS.2006.353148

DO - 10.1109/GENSIPS.2006.353148

M3 - Paper

SP - 45

EP - 46

T2 - 2006 IEEE International Workshop on Genomic Signal Processing and Statstics

Y2 - 28 May 2006 through 30 May 2006

ER -

Modelling of macrophage gene expression in the interferon pathway

Abstract

Conference

Keywords

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