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Journal article
Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network
PloS one, v 12(10), pp e0186134-e0186134
2017
PMID: 29045465
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI) data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment). It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.
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Details
- Title
- Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network
- Creators
- Xianjun Shen - Central China Normal UniversityLi Yi - Central China Normal UniversityXingpeng Jiang - Central China Normal UniversityTingting He - Central China Normal UniversityJincai Yang - Central China Normal UniversityWei Xie - Central China Normal UniversityPo Hu - Central China Normal UniversityXiaohua Hu - Central China Normal University
- Publication Details
- PloS one, v 12(10), pp e0186134-e0186134
- Publisher
- Public LIbrary of Science (PLOS)
- Grant note
- R01 TS000003 / ATSDR CDC HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000413168100038
- Scopus ID
- 2-s2.0-85031786394
- Other Identifier
- 991019167697504721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Biochemical Research Methods