Effect of parameter variations on the inference of context-sensitive probabilisitic boolean networks

S. Marshall, L. Yu, Y. Xiao, E. Dougherty

Research output: Contribution to conferencePaper

Abstract

This paper presents the results of an investigation into the effect of parameter variation on model inference from gene expression data. The models in question are context sensitive Probabilistic Boolean Networks. It is usually necessary to observe a large number of sample points in order to infer the model parameters accurately. This is because the data can become trapped in some fixed point attractor cycles for long time periods. To tackle this problem, a novel sampling strategy for model inference also has been introduced in the paper.

Conference

Conference5th IEEE International Workshop on Genomic Signal Processing and Statistics
Abbreviated titleGENSIPS 2007
CountryFinland
CityTuusula
Period10/06/0712/06/07

Fingerprint

Gene expression
Sampling

Keywords

  • boolean networks
  • parameter variations
  • genomic signal processing
  • inference
  • inference mechanisms

Cite this

Marshall, S., Yu, L., Xiao, Y., & Dougherty, E. (2007). Effect of parameter variations on the inference of context-sensitive probabilisitic boolean networks. 1-4. Paper presented at 5th IEEE International Workshop on Genomic Signal Processing and Statistics , Tuusula, Finland. https://doi.org/10.1109/GENSIPS.2007.4365839
Marshall, S. ; Yu, L. ; Xiao, Y. ; Dougherty, E. / Effect of parameter variations on the inference of context-sensitive probabilisitic boolean networks. Paper presented at 5th IEEE International Workshop on Genomic Signal Processing and Statistics , Tuusula, Finland.5 p.
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abstract = "This paper presents the results of an investigation into the effect of parameter variation on model inference from gene expression data. The models in question are context sensitive Probabilistic Boolean Networks. It is usually necessary to observe a large number of sample points in order to infer the model parameters accurately. This is because the data can become trapped in some fixed point attractor cycles for long time periods. To tackle this problem, a novel sampling strategy for model inference also has been introduced in the paper.",
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Marshall, S, Yu, L, Xiao, Y & Dougherty, E 2007, 'Effect of parameter variations on the inference of context-sensitive probabilisitic boolean networks' Paper presented at 5th IEEE International Workshop on Genomic Signal Processing and Statistics , Tuusula, Finland, 10/06/07 - 12/06/07, pp. 1-4. https://doi.org/10.1109/GENSIPS.2007.4365839

Effect of parameter variations on the inference of context-sensitive probabilisitic boolean networks. / Marshall, S.; Yu, L.; Xiao, Y.; Dougherty, E.

2007. 1-4 Paper presented at 5th IEEE International Workshop on Genomic Signal Processing and Statistics , Tuusula, Finland.

Research output: Contribution to conferencePaper

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Marshall S, Yu L, Xiao Y, Dougherty E. Effect of parameter variations on the inference of context-sensitive probabilisitic boolean networks. 2007. Paper presented at 5th IEEE International Workshop on Genomic Signal Processing and Statistics , Tuusula, Finland. https://doi.org/10.1109/GENSIPS.2007.4365839