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18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)
Precedence Temporal Networks from Gene Expression Data
Dublin, Ireland
June 23-June 24
ISBN: 0-7695-2355-2
ASCII Text
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Lucia Sacchi, Riccardo Bellazzi, Riccardo Porreca, Cristiana Larizza, Paolo Magni, "Precedence Temporal Networks from Gene Expression Data," Computer-Based Medical Systems, IEEE Symposium on, pp. 109-114, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05), 2005.
 
 
BibTex
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@article{ 10.1109/CBMS.2005.83,
author = {Lucia Sacchi and Riccardo Bellazzi and Riccardo Porreca and Cristiana Larizza and Paolo Magni},
title = {Precedence Temporal Networks from Gene Expression Data},
journal ={Computer-Based Medical Systems, IEEE Symposium on},
volume = {0},
year = {2005},
issn = {1063-7125},
pages = {109-114},
doi = {http://doi.ieeecomputersociety.org/10.1109/CBMS.2005.83},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Computer-Based Medical Systems, IEEE Symposium on
TI - Precedence Temporal Networks from Gene Expression Data
SN - 1063-7125
SP109
EP114
A1 - Lucia Sacchi,
A1 - Riccardo Bellazzi,
A1 - Riccardo Porreca,
A1 - Cristiana Larizza,
A1 - Paolo Magni,
PY - 2005
KW - null
VL - 0
JA - Computer-Based Medical Systems, IEEE Symposium on
ER -
 
Lucia Sacchi, University of Pavia
Riccardo Bellazzi, University of Pavia
Riccardo Porreca, University of Pavia
Cristiana Larizza, University of Pavia
Paolo Magni, University of Pavia
In this paper we introduce a novel method to extract from data and graphically represent the temporal relationships between events, called Precedence Temporal Network. The new approach first derives events from time series by exploiting the temporal abstraction technique, then derives temporal precedence between abstractions in terms of association rules and finally expresses the relationships as a labeled graph. The method is applied to the problem of representing the temporal behavior of gene expressions, as they are collected by DNA microarrays. In particular, in this paper we present the results obtained from the analysis of the expression of a subset of the genes involved in cell-cycle regulation.
Citation:
Lucia Sacchi, Riccardo Bellazzi, Riccardo Porreca, Cristiana Larizza, Paolo Magni, "Precedence Temporal Networks from Gene Expression Data," cbms, pp.109-114, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05), 2005
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