article · Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics · 2008
Towards the integration of computational systems biology and high-throughput data: supporting differential analysis of microarray gene expression data
Nicola Segata, Enrico Blanzieri, Corrado Priami
Cited by 4Open access
Abstract
The paradigmatic shift occurred in biology that led first to high-throughput experimental techniques and later to computational systems biology must be applied also to the analysis paradigm of the relation between local models and data to obtain an effective prediction tool. In this work we introduce a unifying notational framework for systems biology models and high-throughput data in order to allow new integrations on the systemic scale like the use of in silico predictions to support the mining of gene expression datasets. Using the framework, we propose two applications concerning the use of system level models to support the differential analysis of microarray expression data. We tested the potentialities of the approach with a specific microarray experiment on the phosphate system in Saccharomyces cerevisiae and a computational model of the PHO pathway that supports the systems biology concepts.
Cite this paper
Segata, N., Blanzieri, E., & Priami, C. (2008). Towards the integration of computational systems biology and high-throughput data: supporting differential analysis of microarray gene expression data. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics, 5(1), 57–71. https://doi.org/10.1515/jib-2008-87
Segata, Nicola, et al. “Towards the integration of computational systems biology and high-throughput data: supporting differential analysis of microarray gene expression data.” Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics, vol. 5, no. 1, 2008, pp. 57–71, https://doi.org/10.1515/jib-2008-87.
Segata, Nicola, Enrico Blanzieri, and Corrado Priami. 2008. “Towards the integration of computational systems biology and high-throughput data: supporting differential analysis of microarray gene expression data.” Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics 5 (1): 57–71. https://doi.org/10.1515/jib-2008-87.
Segata, N., Blanzieri, E. and Priami, C. (2008) ‘Towards the integration of computational systems biology and high-throughput data: supporting differential analysis of microarray gene expression data’, Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics, 5(1), pp. 57–71. Available at: https://doi.org/10.1515/jib-2008-87.
@article{segata2008towards,
title = {{Towards the integration of computational systems biology and high-throughput data: supporting differential analysis of microarray gene expression data}},
author = {Segata, Nicola and Blanzieri, Enrico and Priami, Corrado},
journal = {Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics},
volume = {5},
number = {1},
pages = {57--71},
year = {2008},
doi = {10.1515/jib-2008-87}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.