@inproceedings{9234053829f44fcfa382453bbbb3bfb5,
title = "The intrinsic geometric structure of protein-protein interaction networks for protein interaction prediction",
abstract = "Recent developments in the high-throughput technologies for measuring protein-protein interaction (PPI) have profoundly advanced our ability to systematically infer protein function and regulation. To predict PPI in a net-work, we develop an intrinsic geometry structure (IGS) for the network, which exploits the intrinsic and hidden relationship among proteins in the network through a heat diffusion process. We apply our approach to publicly available PPI network data for the evaluation of the performance of PPI prediction. Experimental results indicate that, under different levels of the missing and spurious PPIs, IGS is able to robustly exploit the intrinsic and hidden relationship for PPI prediction with a higher sensitivity and specificity compared to that of recently proposed methods.",
keywords = "Diffusion Geometry, PPI Network, protein function prediction",
author = "Yi Fang and Mengtian Sun and Guoxian Dai and Karthik Ramani",
year = "2014",
doi = "10.1007/978-3-319-09330-7_56",
language = "English (US)",
isbn = "9783319093291",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "487--493",
booktitle = "Intelligent Computing in Bioinformatics - 10th International Conference, ICIC 2014, Proceedings",
note = "10th International Conference on Intelligent Computing, ICIC 2014 ; Conference date: 03-08-2014 Through 06-08-2014",
}