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Bioinformatics 2006 22(14):e402-e407; doi:10.1093/bioinformatics/btl258
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

Create and assess protein networks through molecular characteristics of individual proteins

Yanay Ofran 1,2,*,{dagger}, Guy Yachdav 1,2,3,{dagger}, Eyal Mozes 2, Ta-tsen Soong 2,4, Rajesh Nair 1,2 and Burkhard Rost 1,2,3

1 Department of Biochemistry and Molecular Biophysics, Columbia University 650 West 168th Street, New York, NY 10032, USA
2 Columbia University Center for Computational Biology and Bioinformatics (C2B2) 1130 St. Nicholas Ave. Rm. 802, New York, NY 10032, USA
3 NorthEast Structural Genomics Consortium (NESG), Columbia University 1130 St. Nicholas Ave. Rm. 802, New York, NY 10032, USA
4 Department of Biomedical Informatics, Columbia University 630 West 168th Street, New York, NY 10032, USA

*To whom correspondence should be addressed.

Motivation: The study of biological systems, pathways and processes relies increasingly on analyses of networks. Most often, such analyses focus on network topology, thereby treating all proteins or genes as identical, featureless nodes. Integrating molecular data and insights about the qualities of individual proteins into the analysis may enhance our ability to decipher biological pathways and processes.

Results: Here, we introduce a novel platform for data integration that generates networks on the macro system-level, analyzes the molecular characteristics of each protein on the micro level, and then combines the two levels by using the molecular characteristics to assess networks. It also annotates the function and subcellular localization of each protein and displays the process on an image of a cell, rendering each protein in its respective cellular compartment. By thus visualizing the network in a cellular context we are able to analyze pathways and processes in a novel way. As an example, we use the system to analyze proteins implicated with Alzheimers disease and show how the integrated view corroborates previous observations and how it helps in the formulation of new hypotheses regarding the molecular underpinnings of the disease.

Availability: http://www.rostlab.org/services/pinat

Contact: pinat{at}rostlab.org; ofran{at}cubic.bioc.columbia.edu


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