Article (Scientific journals)
Designing logical rules to model the response of biomolecular networks with complex interactions: an application to cancer modeling.
Guziolowski, Carito; Blachon, Sylvain; Baumuratova, Tatiana et al.
2011In IEEE/ACM Transactions on Computational Biology and Bioinformatics, 8 (5), p. 1223-34
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Keywords :
Algorithms; Cell Cycle/physiology; Cell Line, Tumor; Computer Simulation; Gene Expression Profiling/methods; Gene Regulatory Networks; Humans; Linear Models; Models, Biological; Oligonucleotide Array Sequence Analysis; Phenotype; Protein Interaction Mapping/methods; Sarcoma, Ewing/genetics/metabolism; Signal Transduction; Systems Biology/methods
Abstract :
[en] We discuss the propagation of constraints in eukaryotic interaction networks in relation to model prediction and the identification of critical pathways. In order to cope with posttranslational interactions, we consider two types of nodes in the network, corresponding to proteins and to RNA. Microarray data provides very lacunar information for such types of networks because protein nodes, although needed in the model, are not observed. Propagation of observations in such networks leads to poor and nonsignificant model predictions, mainly because rules used to propagate information--usually disjunctive constraints--are weak. Here, we propose a new, stronger type of logical constraints that allow us to strengthen the analysis of the relation between microarray and interaction data. We use these rules to identify the nodes which are responsible for a phenotype, in particular for cell cycle progression. As the benchmark, we use an interaction network describing major pathways implied in Ewing's tumor development. The Python library used to obtain our results is publicly available on our supplementary web page.
Disciplines :
Life sciences: Multidisciplinary, general & others
Author, co-author :
Guziolowski, Carito;  University Hospital, Heidelberg
Blachon, Sylvain;  Max-Planck Institute, Potsdam
Baumuratova, Tatiana ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Stoll, Gautier;  Institut Curie, Paris
Radulescu, Ovidiu;  Universie de Montpelier 2
Siegel, Anne;  University of Rennes 1, Rennes
Language :
English
Title :
Designing logical rules to model the response of biomolecular networks with complex interactions: an application to cancer modeling.
Publication date :
2011
Journal title :
IEEE/ACM Transactions on Computational Biology and Bioinformatics
ISSN :
1557-9964
Publisher :
IEEE Computer Society, United States - New York
Volume :
8
Issue :
5
Pages :
1223-34
Peer reviewed :
Peer Reviewed verified by ORBi
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