Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.
Sci. Signal., 28 July 2009
Vol. 2, Issue 81, p. ra40
[DOI: 10.1126/scisignal.2000350]
RESEARCH ARTICLES
Integrating Proteomic, Transcriptional, and Interactome Data Reveals Hidden Components of Signaling and Regulatory Networks
Shao-shan Carol Huang1 and
Ernest Fraenkel2,3*
1 Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. 2 Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. 3 Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge MA 02139, USA.
Abstract:
Cellular signaling and regulatory networks underlie fundamental biological processes such as growth, differentiation, and response to the environment. Although there are now various high-throughput methods for studying these processes, knowledge of them remains fragmentary. Typically, the majority of hits identified by transcriptional, proteomic, and genetic assays lie outside of the expected pathways. These unexpected components of the cellular response are often the most interesting, because they can provide new insights into biological processes and potentially reveal new therapeutic approaches. However, they are also the most difficult to interpret. We present a technique, based on the Steiner tree problem, that uses previously reported protein-protein and protein-DNA interactions to determine how these hits are organized into functionally coherent pathways, revealing many components of the cellular response that are not readily apparent in the original data. Applied simultaneously to phosphoproteomic and transcriptional data for the yeast pheromone response, it identifies changes in diverse cellular processes that extend far beyond the expected pathways.
* To whom correspondence should be addressed. E-mail: fraenkel-admin{at}mit.edu
Citation: S.-s. C. Huang, E. Fraenkel, Integrating Proteomic, Transcriptional, and Interactome Data Reveals Hidden Components of Signaling and Regulatory Networks. Sci. Signal.2, ra40 (2009).
The editors suggest the following Related Resources on Science sites:
In Science Signaling
EDITORS' CHOICE
John F. Foley (15 May 2012) Sci. Signal.5 (224), ec135.
[DOI: 10.1126/scisignal.2003217] |Abstract »
EDITORIAL GUIDES
Nancy R. Gough (6 September 2011) Sci. Signal.4 (189), eg8.
[DOI: 10.1126/scisignal.2002478] |Abstract »|Full Text »|PDF »
RESEARCH RESOURCES
Arunachalam Vinayagam, Ulrich Stelzl, Raphaele Foulle, Stephanie Plassmann, Martina Zenkner, Jan Timm, Heike E. Assmus, Miguel A. Andrade-Navarro, and Erich E. Wanker (6 September 2011) Sci. Signal.4 (189), rs8.
[DOI: 10.1126/scisignal.2001699] |Editor's Summary »|Abstract »|Full Text »|PDF »|Supplementary Materials »
MEETING REPORTS
Robert J. Prill, Julio Saez-Rodriguez, Leonidas G. Alexopoulos, Peter K. Sorger, and Gustavo Stolovitzky (6 September 2011) Sci. Signal.4 (189), mr7.
[DOI: 10.1126/scisignal.2002212] |Abstract »|Full Text »|PDF »
PRESENTATIONS
Illés J. Farkas, Tamás Korcsmáros, István A. Kovács, Ágoston Mihalik, Robin Palotai, Gábor I. Simkó, Kristóf Z. Szalay, Máté Szalay-Beko, Tibor Vellai, Shijun Wang, and Peter Csermely (17 May 2011) Sci. Signal.4 (173), pt3.
[DOI: 10.1126/scisignal.2001950] |Abstract »|Full Text »|PDF »|Slideshow »
EDITORIAL GUIDES
Nancy R. Gough and Michael B. Yaffe (15 February 2011) Sci. Signal.4 (160), eg2.
[DOI: 10.1126/scisignal.2001871] |Abstract »|Full Text »|PDF »
RESEARCH ARTICLES
Tian-Rui Xu, Vladislav Vyshemirsky, Amélie Gormand, Alex von Kriegsheim, Mark Girolami, George S. Baillie, Dominic Ketley, Allan J. Dunlop, Graeme Milligan, Miles D. Houslay, and Walter Kolch (16 March 2010) Sci. Signal.3 (113), ra20.
[DOI: 10.1126/scisignal.2000517] |Editor's Summary »|Abstract »|Full Text »|PDF »|Supplementary Materials »
A Directed Protein Interaction Network for Investigating Intracellular Signal Transduction.
A. Vinayagam, U. Stelzl, R. Foulle, S. Plassmann, M. Zenkner, J. Timm, H. E. Assmus, M. A. Andrade-Navarro, and E. E. Wanker (2011)
Science Signaling
4, rs8
|Abstract »|Full Text »|PDF »
ResponseNet: revealing signaling and regulatory networks linking genetic and transcriptomic screening data.
A. Lan, I. Y. Smoly, G. Rapaport, S. Lindquist, E. Fraenkel, and E. Yeger-Lotem (2011)
Nucleic Acids Res.
39, W424-W429
|Abstract »|Full Text »|PDF »
Integrating Multiple Types of Data for Signaling Research: Challenges and Opportunities.
Finding undetected protein associations in cell signaling by belief propagation.
M. Bailly-Bechet, C. Borgs, A. Braunstein, J. Chayes, A. Dagkessamanskaia, J.- M. Francois, and R. Zecchina (2011)
PNAS
108, 882-887
|Abstract »|Full Text »|PDF »
Cancer systems biology: a network modeling perspective.