Combining Network Modeling and Gene Expression Microarray Analysis to Explore the Dynamics of Th1 and Th2 Cell Regulation
| العنوان: | Combining Network Modeling and Gene Expression Microarray Analysis to Explore the Dynamics of Th1 and Th2 Cell Regulation |
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| المؤلفون: | Filippo Castiglione, Daniele Santoni, Eivind Hovig, Mikael Benson, Trevor Clancy, Kartiek Kanduri, Fredrik Barrenäs, Marco Pedicini |
| المساهمون: | Pedicini, Marco, Barrenäs, F, Clancy, T, Castiglione, F, Hovig, E, Kanduri, K, Santoni, D, Benson, M. |
| المصدر: | PLoS Computational Biology; Vol 6 PLoS Computational Biology PLoS Computational Biology, Vol 6, Iss 12, p e1001032 (2010) PLoS computational biology 6 (2010): 1–8. doi:10.1371/journal.pcbi.1001032 info:cnr-pdr/source/autori:PEDICINI M, BARRENÄS F, CLANCY T, CASTIGLIONE F, HOVIG E, KANDURI K, SANTONI D, BENSON M/titolo:Combining network modeling and gene expression microarray analysis to explore the dynamics of Th1 and Th2 cell regulation/doi:10.1371%2Fjournal.pcbi.1001032/rivista:PLoS computational biology/anno:2010/pagina_da:1/pagina_a:8/intervallo_pagine:1–8/volume:6 |
| بيانات النشر: | PUBLIC LIBRARY SCIENCE, 2010. |
| سنة النشر: | 2010 |
| مصطلحات موضوعية: | In silico, Gene regulatory network, Biology, Transcriptome, Gene Knockout Techniques, 03 medical and health sciences, Cellular and Molecular Neuroscience, Th2 Cells, Databases, Genetic, Genetics, Humans, Computer Simulation, Gene Regulatory Networks, lcsh:QH301-705.5, Molecular Biology, Gene, Ecology, Evolution, Behavior and Systematics, Gene knockout, Oligonucleotide Array Sequence Analysis, 030304 developmental biology, 0303 health sciences, Computational Biology/Systems Biology, Ecology, Gene Expression Profiling, 030302 biochemistry & molecular biology, Computational Biology, Th1 Cells, Phenotype, Gene expression profiling, lcsh:Biology (General), Computational Theory and Mathematics, Modeling and Simulation, Immunology/Genetics of the Immune System, Mathematics, Algorithms, Research Article |
| الوصف: | Two T helper (Th) cell subsets, namely Th1 and Th2 cells, play an important role in inflammatory diseases. The two subsets are thought to counter-regulate each other, and alterations in their balance result in different diseases. This paradigm has been challenged by recent clinical and experimental data. Because of the large number of genes involved in regulating Th1 and Th2 cells, assessment of this paradigm by modeling or experiments is difficult. Novel algorithms based on formal methods now permit the analysis of large gene regulatory networks. By combining these algorithms with in silico knockouts and gene expression microarray data from human T cells, we examined if the results were compatible with a counter-regulatory role of Th1 and Th2 cells. We constructed a directed network model of genes regulating Th1 and Th2 cells through text mining and manual curation. We identified four attractors in the network, three of which included genes that corresponded to Th0, Th1 and Th2 cells. The fourth attractor contained a mixture of Th1 and Th2 genes. We found that neither in silico knockouts of the Th1 and Th2 attractor genes nor gene expression microarray data from patients with immunological disorders and healthy subjects supported a counter-regulatory role of Th1 and Th2 cells. By combining network modeling with transcriptomic data analysis and in silico knockouts, we have devised a practical way to help unravel complex regulatory network topology and to increase our understanding of how network actions may differ in health and disease. Author Summary Different T helper (Th) cell subsets have an important role in regulating the immune response in inflammatory diseases. Th1 and Th2 cells are thought to counter-regulate each other, and alterations in their balance result in different diseases.This paradigm has been challenged by recent clinical and experimental data. Because of the large number of genes involved in regulating Th1 and Th2 cells, assessment of this paradigm by experiments or modelling is difficult. In this study, we combined novel algorithms for network analysis, in silico knockouts, and gene expression microarrays to examine if Th1 and Th2 cells had counter-regulatory roles. We constructed a directed network model of genes that regulated Th1 and Th2 cells through text mining and manual curation. We identified four cycles in the gene expression dynamics, three of which expressed genes that corresponded to Th0 (Th1/Th2 precursor), Th1 and Th2 cells. The fourth cycle contained the expression of a mixture of Th1 and Th2 genes. We found that neither in silico knockouts of the Th1 and Th2 attractor genes nor gene expression microarray data from patients and healthy subjects supported a counter-regulatory role of Th1 and Th2 cells. |
| اللغة: | English |
| تدمد: | 1553-7358 |
| DOI: | 10.1371/journal.pcbi.1001032 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e582adef0639fdb93707a52655cf8337Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....e582adef0639fdb93707a52655cf8337 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15537358 |
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| DOI: | 10.1371/journal.pcbi.1001032 |