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The network organization of cancer-associated protein complexes in human tissues
Umeå University, Faculty of Science and Technology, Department of Physics. (IceLab)ORCID iD: 0000-0003-2156-1096
2013 (English)In: Scientific Reports, ISSN 2045-2322, Vol. 3, 1583- p.Article in journal (Refereed) Published
Abstract [en]

Differential gene expression profiles for detecting disease genes have been studied intensively in systems biology. However, it is known that various biological functions achieved by proteins follow from the ability of the protein to form complexes by physically binding to each other. In other words, the functional units are often protein complexes rather than individual proteins. Thus, we seek to replace the perspective of disease-related genes by disease-related complexes, exemplifying with data on 39 human solid tissue cancers and their original normal tissues. To obtain the differential abundance levels of protein complexes, we apply an optimization algorithm to genome-wide differential expression data. From the differential abundance of complexes, we extract tissue- and cancer-selective complexes, and investigate their relevance to cancer. The method is supported by a clustering tendency of bipartite cancer-complex relationships, as well as a more concrete and realistic approach to disease-related proteomics.

Place, publisher, year, edition, pages
2013. Vol. 3, 1583- p.
National Category
Bioinformatics and Systems Biology
URN: urn:nbn:se:umu:diva-67983DOI: 10.1038/srep01583OAI: diva2:615202
Swedish Research Council, 2012-3651
Available from: 2013-04-09 Created: 2013-04-09 Last updated: 2013-09-06Bibliographically approved

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