Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractPlant production of volatile semiochemicals in response to insect-derived elicitors    Next AbstractSimultaneous Occurrence of Vapochromism and Vapoluminescence in Formaldehyde-Responsive Amino-Functionalized Copper(I) Polymorphic Coordination Polymers »

J Comput Biol


Title:Simultaneous reconstruction of multiple signaling pathways via the prize-collecting steiner forest problem
Author(s):Tuncbag N; Braunstein A; Pagnani A; Huang SS; Chayes J; Borgs C; Zecchina R; Fraenkel E;
Address:"Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA"
Journal Title:J Comput Biol
Year:2013
Volume:20
Issue:2
Page Number:124 - 136
DOI: 10.1089/cmb.2012.0092
ISSN/ISBN:1557-8666 (Electronic) 1066-5277 (Print) 1066-5277 (Linking)
Abstract:"Signaling and regulatory networks are essential for cells to control processes such as growth, differentiation, and response to stimuli. Although many 'omic' data sources are available to probe signaling pathways, these data are typically sparse and noisy. Thus, it has been difficult to use these data to discover the cause of the diseases and to propose new therapeutic strategies. We overcome these problems and use 'omic' data to reconstruct simultaneously multiple pathways that are altered in a particular condition by solving the prize-collecting Steiner forest problem. To evaluate this approach, we use the well-characterized yeast pheromone response. We then apply the method to human glioblastoma data, searching for a forest of trees, each of which is rooted in a different cell-surface receptor. This approach discovers both overlapping and independent signaling pathways that are enriched in functionally and clinically relevant proteins, which could provide the basis for new therapeutic strategies. Although the algorithm was not provided with any information about the phosphorylation status of receptors, it identifies a small set of clinically relevant receptors among hundreds present in the interactome"
Keywords:"*Algorithms Brain Neoplasms/*genetics Cell Communication Gene Expression Profiling Gene Regulatory Networks Glioblastoma/*genetics Humans Models, Biological Neoplasm Proteins/*genetics Pharmacogenetics Pheromones/*genetics Protein Interaction Mapping/stat;"
Notes:"MedlineTuncbag, Nurcan Braunstein, Alfredo Pagnani, Andrea Huang, Shao-Shan Carol Chayes, Jennifer Borgs, Christian Zecchina, Riccardo Fraenkel, Ernest eng R01 GM089903/GM/NIGMS NIH HHS/ R01GM089903/GM/NIGMS NIH HHS/ U54CA112967/CA/NCI NIH HHS/ Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. 2013/02/07 J Comput Biol. 2013 Feb; 20(2):124-36. doi: 10.1089/cmb.2012.0092"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 26-12-2024