ArticleScientific reports2013
The network organization of cancer-associated protein complexes in human tissues.
Article in Scientific reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 37 citations in OpenAlex.
- Tumor relevant protein functional interactions identified using bipartite graph analyses.Scientific reports · 2021Article
- Biomolecular condensation of NUP98 fusion proteins drives leukemogenic gene expression.Nature structural & molecular biology · 2021Article
- Differential analysis of combinatorial protein complexes with CompleXChange.BMC bioinformatics · 2019Article
- An integer programming framework for inferring disease complexes from network data.Bioinformatics (Oxford, England) · 2016Article
- Cell type-specific properties and environment shape tissue specificity of cancer genes.Scientific reports · 2016Article
- SPECTRA: An Integrated Knowledge Base for Comparing Tissue and Tumor-Specific PPI Networks in Human.Frontiers in bioengineering and biotechnology · 2015Article
- Molecular Recognition of Human Liver Cancer Cells Using DNA Aptamers Generated via Cell-SELEX.PloS one · 2015Article
- A novel method for identifying disease associated protein complexes based on functional similarity protein complex networks.Algorithms for molecular biology : AMB · 2015Article
- A multiobjective approach for identifying protein complexes and studying their association in multiple disorders.Algorithms for molecular biology : AMB · 2015Article
- Complex-based analysis of dysregulated cellular processes in cancer.BMC systems biology · 2014Article
- Prioritizing protein complexes implicated in human diseases by network optimization.BMC systems biology · 2014Article
- Box-covering algorithm for fractal dimension of weighted networks.Scientific reports · 2013Article
- Bioinformatics analysis for the antirheumatic effects of huang-lian-jie-du-tang from a network perspective.Evidence-based complementary and alternative medicine : eCAM · 2013Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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