| Item Type: | Article | |
|---|---|---|
| MIUR type: | Article > Journal article | |
| Title: | A Prize-Collecting Steiner Tree Approach for Transduction Network Inference | |
| Authors string: | M. Bailly-Bechet; A. Braunstein; R. Zecchina | |
| University authors: | ||
| Journal or Publication Title: | LECTURE NOTES IN COMPUTER SCIENCE | |
| Referee type: | Not specified type | |
| Publisher: | Springer | |
| Volume: | 5688 | |
| Page Range: | pp. 83-95 | |
| Number of Pages: | 13 | |
| ISSN: | 0302-9743 | |
| Description/Info: | Into the cell, information from the environment is mainly propagated via signaling pathways which form a transduction network. Here we propose a new algorithm to infer transduction networks from heterogeneous data, using both the protein interaction network and expression datasets. We formulate the inference problem as an optimization task, and develop a message-passing, probabilistic and distributed formalism to solve it. We apply our algorithm to the pheromone response in the baker's yeast S. cerevisiae. We are able to find the backbone of the known structure of the MAPK cascade of pheromone response, validating our algorithm. More importantly, we make biological predictions about some proteins whose role could be at the interface between pheromone response and other cellular functions | |
| Date: | 2009 | |
| Status: | Published | |
| Language of publication: | English | |
| Uncontrolled Keywords: | ||
| Departments (original): | DIFIS - Physics | |
| Departments: | DISAT - Department of Applied Science and Technology | |
| Related URLs: | ||
| Subjects: | Area 02 - Scienze fisiche > FISICA TEORICA, MODELLI E METODI MATEMATICI | |
| Date Deposited: | 15 Dec 2009 16:12 | |
| Last Modified: | 06 Oct 2012 08:19 | |
| Id Number (DOI): | 10.1007/978-3-642-03845-7_6 | |
| Permalink: | http://porto.polito.it/id/eprint/2294450 | |
| Linksolver URL: | ![]() |
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