Protein complex prediction by date hub removal. (June 2018)
- Record Type:
- Journal Article
- Title:
- Protein complex prediction by date hub removal. (June 2018)
- Main Title:
- Protein complex prediction by date hub removal
- Authors:
- Pyrogova, Iana
Wong, Limsoon - Abstract:
- Graphical abstract: Highlights: The date hub proteins tend to occur within the intersection of real overlapping protein complexes. We demonstrated that degree and transitivity can be used to predict a reliable list of date hub proteins. A complex discovery algorithm after removing date hubs from PPI networks recalls more overlapping complexes that were missed earlier. We proposed the "double-barrel strategy" to combine the complexes predicted before and after we remove date hubs. Abstract: Proteins physically interact with each other and form protein complexes to perform their biological functions. The prediction of protein complexes from protein–protein interaction (PPI) network is usually difficult when the complexes are overlapping with each other in a dense region of the network. To address the problem of predicting overlapping complexes, a previously proposed network–decomposition approach is promising. It decomposes a PPI network by e.g. removing proteins with high degree (hubs) which may participate in different complexes. This motivates us to examine a list of proteins, which bind their different partners at different time or at different location (viz. date hubs), manually collected from literature, for network decomposition. Results show that the CMC complex discovery algorithm after removing date hubs recalls more overlapping complexes that were missed earlier. Further improvement in performance is achieved when we predict date hub proteins based on simple networkGraphical abstract: Highlights: The date hub proteins tend to occur within the intersection of real overlapping protein complexes. We demonstrated that degree and transitivity can be used to predict a reliable list of date hub proteins. A complex discovery algorithm after removing date hubs from PPI networks recalls more overlapping complexes that were missed earlier. We proposed the "double-barrel strategy" to combine the complexes predicted before and after we remove date hubs. Abstract: Proteins physically interact with each other and form protein complexes to perform their biological functions. The prediction of protein complexes from protein–protein interaction (PPI) network is usually difficult when the complexes are overlapping with each other in a dense region of the network. To address the problem of predicting overlapping complexes, a previously proposed network–decomposition approach is promising. It decomposes a PPI network by e.g. removing proteins with high degree (hubs) which may participate in different complexes. This motivates us to examine a list of proteins, which bind their different partners at different time or at different location (viz. date hubs), manually collected from literature, for network decomposition. Results show that the CMC complex discovery algorithm after removing date hubs recalls more overlapping complexes that were missed earlier. Further improvement in performance is achieved when we predict date hub proteins based on simple network features and remove them from PPI networks. … (more)
- Is Part Of:
- Computational biology and chemistry. Volume 74(2018)
- Journal:
- Computational biology and chemistry
- Issue:
- Volume 74(2018)
- Issue Display:
- Volume 74, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 74
- Issue:
- 2018
- Issue Sort Value:
- 2018-0074-2018-0000
- Page Start:
- 407
- Page End:
- 419
- Publication Date:
- 2018-06
- Subjects:
- Protein complex prediction -- PPI networks -- PPI network decomposition -- Date hub proteins
Chemistry -- Data processing -- Periodicals
Biology -- Data processing -- Periodicals
Biochemistry -- Data processing
Biology -- Data processing
Molecular biology -- Data processing
Periodicals
Electronic journals
542.85 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14769271 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compbiolchem.2018.03.012 ↗
- Languages:
- English
- ISSNs:
- 1476-9271
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3390.576700
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 13023.xml