oru.sePublikationer
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
ExprEssence: revealing the essence of differential experimental data in the context of an interaction/regulation net-work
Institute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Rostock, Germany; Institute for Anatomy and Cell Biology, Ernst Moritz Arndt University Greifswald, Greifswald, Germany; Institute for Anatomy and Cell Biology, Ernst Moritz Arndt University Greifswald, Greifswald, Germany .
Department of Cell and Developmental Biology, Max Planck Institute for Molecular Biomedicine, Münster, Germany .
Institute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Rostock, Germany .
Institute for Biostatistics and Informatics in Medicine and Ageing Research, University of Rostock, Rostock, Germany .
Show others and affiliations
2010 (English)In: BMC Systems Biology, ISSN 1752-0509, Vol. 4, 164- p., 164Article in journal (Refereed) Published
Abstract [en]

Background: Experimentalists are overwhelmed by high-throughput data and there is an urgent need to condense information into simple hypotheses. For example, large amounts of microarray and deep sequencing data are becoming available, describing a variety of experimental conditions such as gene knockout and knockdown, the effect of interventions, and the differences between tissues and cell lines.

Results: To address this challenge, we developed a method, implemented as a Cytoscape plugin called ExprEssence. As input we take a network of interaction, stimulation and/or inhibition links between genes/proteins, and differential data, such as gene expression data, tracking an intervention or development in time. We condense the network, highlighting those links across which the largest changes can be observed. Highlighting is based on a simple formula inspired by the law of mass action. We can interactively modify the threshold for highlighting and instantaneously visualize results. We applied ExprEssence to three scenarios describing kidney podocyte biology, pluripotency and ageing: 1) We identify putative processes involved in podocyte (de-)differentiation and validate one prediction experimentally. 2) We predict and validate the expression level of a transcription factor involved in pluripotency. 3) Finally, we generate plausible hypotheses on the role of apoptosis, cell cycle deregulation and DNA repair in ageing data obtained from the hippocampus.

Conclusion: Reducing the size of gene/protein networks to the few links affected by large changes allows to screen for putative mechanistic relationships among the genes/proteins that are involved in adaptation to different experimental conditions, yielding important hypotheses, insights and suggestions for new experiments. We note that we do not focus on the identification of 'active subnetworks'. Instead we focus on the identification of single links (which may or may not form subnetworks), and these single links are much easier to validate experimentally than submodules. ExprEssence is available at http://sourceforge.net/projects/expressence/.

Place, publisher, year, edition, pages
London, UK: BioMed Central, 2010. Vol. 4, 164- p., 164
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:oru:diva-40626DOI: 10.1186/1752-0509-4-164ISI: 000285723200001PubMedID: 21118483Scopus ID: 2-s2.0-78649489546OAI: oai:DiVA.org:oru-40626DiVA: diva2:778002
Available from: 2015-01-09 Created: 2015-01-09 Last updated: 2015-03-13Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMedScopus

Search in DiVA

By author/editor
Repsilber, Dirk
In the same journal
BMC Systems Biology
Bioinformatics and Systems Biology

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 20 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf