Protein complex prediction via bottleneck-based graph partitioning
- Authors
- Ahn, J.; Lee, D.H.; Yoon, Y.; Yeu, Y.; Park, S.
- Issue Date
- 2012
- Keywords
- Bottleneck protein; Network clustering; Protein complex detection; Protein-protein interaction
- Citation
- International Conference on Information and Knowledge Management, Proceedings, pp.49 - 55
- Journal Title
- International Conference on Information and Knowledge Management, Proceedings
- Start Page
- 49
- End Page
- 55
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/17522
- DOI
- 10.1145/2390068.2390079
- ISSN
- 0000-0000
- Abstract
- Detecting protein complexes is one of essential and fundamental tasks in understanding various biological functions or processes. Therefore, precise identification of protein complexes is indispensible. For more precise detection of protein complexes, we propose a novel data structure which employs bottleneck proteins as partitioning points for detecting the protein complexes. The partitioning process allows overlapping between resulting protein complexes. We applied our algorithm to several PPI (Protein-Protein Interaction) networks of Saccharomyces cerevisiae and Homo sapiens, and validated our results using public databases of protein complexes. Our algorithm resulted in overlapping protein complexes with significantly improved F1 score, which comes from higher precision.
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Collections - IT융합대학 > 컴퓨터공학과 > 1. Journal Articles
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