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Integrated network analysis of transcriptomic and proteomic data in psoriasis

Eleonora Piruzian1, Sergey Bruskin1, Alex Ishkin12*, Rustam Abdeev3, Sergey Moshkovskii4, Stanislav Melnik4, Yuri Nikolsky2 and Tatiana Nikolskaya12

Author Affiliations

1 Vavilov Institute of General Genetics, Russian Academy of Sciences, Gubkina St, 3 GSP-1, 119991 Moscow, Russia

2 GeneGo, Inc, Saint Joseph, MI, USA

3 Center for Theoretical Problems of Physico-Chemical Pharmacology, Russian Academy of Sciences, Kosigina str, 4, 119991 Moscow, Russia

4 Institute of Biomedical Chemistry, Russian Academy of Medical Sciences, 10 Pogodinskaya st, 119121 Moscow, Russia

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BMC Systems Biology 2010, 4:41  doi:10.1186/1752-0509-4-41

Published: 8 April 2010



Psoriasis is complex inflammatory skin pathology of autoimmune origin. Several cell types are perturbed in this pathology, and underlying signaling events are complex and still poorly understood.


In order to gain insight into molecular machinery underlying the disease, we conducted a comprehensive meta-analysis of proteomics and transcriptomics of psoriatic lesions from independent studies. Network-based analysis revealed similarities in regulation at both proteomics and transcriptomics level. We identified a group of transcription factors responsible for overexpression of psoriasis genes and a number of previously unknown signaling pathways that may play a role in this process. We also evaluated functional synergy between transcriptomics and proteomics results.


We developed network-based methodology for integrative analysis of high throughput data sets of different types. Investigation of proteomics and transcriptomics data sets on psoriasis revealed versatility in regulatory machinery underlying pathology and showed complementarities between two levels of cellular organization.