Change search
ReferencesLink to record
Permanent link

Direct link
Prognostic significance in breast cancer of a gene signature capturing stromal PDGF signaling
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
Show others and affiliations
(English)In: American Journal of Pathology, ISSN 0002-9440, E-ISSN 1525-2191Article in journal (Refereed) Accepted
National Category
Bioinformatics (Computational Biology)
Research subject
Biochemistry with Emphasis on Theoretical Chemistry
URN: urn:nbn:se:su:diva-89054OAI: diva2:615429
Available from: 2013-04-10 Created: 2013-04-10 Last updated: 2013-04-11Bibliographically approved
In thesis
1. Network and gene expression analyses for understanding protein function
Open this publication in new window or tab >>Network and gene expression analyses for understanding protein function
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Biological function is the result of a complex network of functional associations between genes or their products. Modeling the dynamics underlying biological networks is one of the big challenges in bioinformatics. A first step towards solving this problem is to predict and study the networks of functional associations underlying various conditions.

An improved version of the FunCoup network inference method that features networks for three new species and updated versions of the existing networks is presented. Network clustering, i.e. partitioning networks into highly connected components is an important tool for network analysis. We developed MGclus, a clustering method for biological networks that scores shared network neighbors. We found MGclus to perform favorably compared to other methods popular in the field. Studying sets of experimentally derived genes in the context of biological networks is a common strategy to shed light on their underlying biology. The CrossTalkZ method presented in this work assesses the statistical significance of crosstalk enrichment, i.e. the extent of connectivity between or within groups of functionally coupled genes or proteins in biological networks. We further demonstrate that CrossTalkZ is a valuable method to functionally annotate experimentally derived gene sets.

Males and females differ in the expression of an extensive number of genes. The methods developed in the first part of this work were applied to study sex-biased genes in chicken and several network properties related to the molecular mechanisms of sex-biased gene regulation in chicken were deduced. Cancer studies have shown that tumor progression is strongly determined by the tumor microenvironment. We derived a gene expression signature of PDGF-activated fibroblasts that shows a strong prognostic significance in breast cancer in univariate and multivariate survival analyses when compared to established markers for prognosis.

Place, publisher, year, edition, pages
Stockholm: Department of Biochemistry and Biophysics, Stockholm University, 2013. 86 p.
biological networks, network inference, network analysis, clustering, network module, network crosstalk, expression analysis, gene signature, biomarker
National Category
Bioinformatics (Computational Biology)
Research subject
Biochemistry with Emphasis on Theoretical Chemistry
urn:nbn:se:su:diva-89055 (URN)978-91-7447-674-3 (ISBN)
Public defence
2013-05-23, Nordenskiöldsalen, Geovetenskapens hus, Svante Arrhenius väg 12, Stockholm, 09:00 (English)

At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 5: Accepted.


Available from: 2013-05-01 Created: 2013-04-10 Last updated: 2013-04-22Bibliographically approved

Open Access in DiVA

No full text

Search in DiVA

By author/editor
Frings, OliverSonnhammer, Erik
By organisation
Department of Biochemistry and BiophysicsScience for Life Laboratory (SciLifeLab)
In the same journal
American Journal of Pathology
Bioinformatics (Computational Biology)

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 50 hits
ReferencesLink to record
Permanent link

Direct link