English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  A computational framework for boosting confidence in high-throughput protein-protein interaction datasets

Hosur, R., Peng, J., Vinayagam, A., Stelzl, U., Xu, J., Perrimon, N., et al. (2012). A computational framework for boosting confidence in high-throughput protein-protein interaction datasets. Genome Biology, 13(8), R76-R76. doi:10.1186/gb-2012-13-8-r76.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-000E-E7AC-7 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-000E-E7AD-5
Genre: Journal Article

Files

show Files
hide Files
:
Hosur.pdf (Publisher version), 2MB
Name:
Hosur.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
© 2012 Hosur et al.; licensee BioMed Central Ltd
License:
-

Locators

show

Creators

show
hide
 Creators:
Hosur, R., Author
Peng, J., Author
Vinayagam, A., Author
Stelzl, U.1, Author              
Xu, J., Author
Perrimon, N., Author
Bienkowska, J., Author
Berger, B., Author
Affiliations:
1Molecular Interaction Networks (Ulrich Stelzl), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479660              

Content

show
hide
Free keywords: -
 Abstract: Improving the quality and coverage of the protein interactome is of tantamount importance for biomedical research, particularly given the various sources of uncertainty in high-throughput techniques. We introduce a structure-based framework, Coev2Net, for computing a single confidence score that addresses both false-positive and false-negative rates. Coev2Net is easily applied to thousands of binary protein interactions and has superior predictive performance over existing methods. We experimentally validate selected high-confidence predictions in the human MAPK network and show that predicted interfaces are enriched for cancer -related or damaging SNPs. Coev2Net can be downloaded at http://struct2net.csail.mit.edu.

Details

show
hide
Language(s): eng - English
 Dates: 2012-08-312012
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1186/gb-2012-13-8-r76
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Genome Biology
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: London : BioMed Central Ltd.
Pages: - Volume / Issue: 13 (8) Sequence Number: - Start / End Page: R76 - R76 Identifier: ISSN: 1465-6906
CoNE: /journals/resource/1000000000224390_1