کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5513580 1541216 2016 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Identifying protein complexes based on brainstorming strategy
ترجمه فارسی عنوان
شناسایی پروتئین های پیچیده بر اساس استراتژی طوفان مغزی
کلمات کلیدی
شبکه متقابل پروتئین-پروتئین، پروتئین پیچیده، استراتژی طوفان مغزی، هسته شناسی ژن،
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی زیست شیمی
چکیده انگلیسی


- IPC-BSS algorithm based on brainstorming strategy is proposed.
- Node distance is defined by combining the gene ontology information.
- Clustering center nodes are selected to form initial clusters.
- Initial clusters are optimized in two situations to form the protein complexes.
- IPC-BSS algorithm outperforms the classic clustering algorithms.

Protein complexes comprising of interacting proteins in protein-protein interaction network (PPI network) play a central role in driving biological processes within cells. Recently, more and more swarm intelligence based algorithms to detect protein complexes have been emerging, which have become the research hotspot in proteomics field. In this paper, we propose a novel algorithm for identifying protein complexes based on brainstorming strategy (IPC-BSS), which is integrated into the main idea of swarm intelligence optimization and the improved K-means algorithm. Distance between the nodes in PPI network is defined by combining the network topology and gene ontology (GO) information. Inspired by human brainstorming process, IPC-BSS algorithm firstly selects the clustering center nodes, and then they are separately consolidated with the other nodes with short distance to form initial clusters. Finally, we put forward two ways of updating the initial clusters to search optimal results. Experimental results show that our IPC-BSS algorithm outperforms the other classic algorithms on yeast and human PPI networks, and it obtains many predicted protein complexes with biological significance.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Methods - Volume 110, 1 November 2016, Pages 44-53
نویسندگان
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