@inproceedings{52e89bedc6ab4346bd3a3e822dfae42b,
title = "Mining maximal dense subgraphs in uncertain PPI network",
abstract = "Several studies have shown that the prediction of protein function using PPI data is promising. However, the PPI data generated from experiments are noisy, incomplete and inaccurate, which promotes to represent PPI dataset as an uncertain graph. In this paper, we proposed a novel algorithm to mine maximal dense subgraphs efficiently in uncertain PPI network. It adopted several techniques to achieve efficient mining. An extensive experimental evaluation on yeast PPI network demonstrated that our approach had good performance in terms of precision and efficiency.",
keywords = "Dense subgraph, Expected density, PPI, Uncertain graph",
author = "Jiacai Liu and Xuequn Shang and Ya Meng and Miao Wang",
year = "2012",
doi = "10.4028/www.scientific.net/AMM.135-136.609",
language = "英语",
isbn = "9783037852903",
series = "Applied Mechanics and Materials",
pages = "609--615",
booktitle = "Advances in Science and Engineering II",
note = "2011 WASE Global Conference on Science Engineering, GCSE 2011 ; Conference date: 10-12-2011 Through 11-12-2011",
}