Orkun S SoyerSummaryAffiliation: Swiss Federal Institute of Technology Country: Switzerland Publications
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Publications
Signal transduction networks: topology, response and biochemical processesOrkun S Soyer
Theoretical Biology Group, Ecology and Evolution, Swiss Federal Institute of Technology ETH, Zurich, Switzerland
J Theor Biol 238:416-25. 2006..Furthermore it shows that network topology plays a key role on determining response type and properties and that proper representation of network topology is crucial to discover and understand so-called building blocks of large networks...
Simulating the evolution of signal transduction pathwaysOrkun S Soyer
Theoretical Biology Group, Ecology and Evolution, CH 8092, Zurich, Switzerland
J Theor Biol 241:223-32. 2006..We conclude that simulating the evolution of signal transduction networks to mediate a certain behavior may be a promising approach for understanding the general properties of the natural pathway for that behavior...
Evolution of complexity in signaling pathwaysOrkun S Soyer
Theoretical Biology Group, Institute for Integrative Biology, Swiss Federal Institute of Technology ETH, Universitatsstrasse 16, ETH Zentrum, CHN K12 2, CH 8092 Zurich, Switzerland
Proc Natl Acad Sci U S A 103:16337-42. 2006..This leads to the counterintuitive conclusion that simple response requirements on a pathway would facilitate its evolution toward higher complexity...
The evolution of connectivity in metabolic networksThomas Pfeiffer
Computational Laboratory, ETH Zurich, Zurich, Switzerland
PLoS Biol 3:e228. 2005..Specifically, our simulations indicate that group transfer reactions are essential for the emergence of hubs...
Emergence and maintenance of functional modules in signaling pathwaysOrkun S Soyer
The Microsoft Research University of Trento Centre for Computational and Systems Biology CoSBi, Piazza Manci 17, 38100 Povo Trento, Italy
BMC Evol Biol 7:205. 2007..e. environment) in order for modularity to emerge. Here, we provide an alternative and simpler explanation using a realistic model of biological signaling pathways and simulating their evolution...
Predicting functional sites in proteins: site-specific evolutionary models and their application to neurotransmitter transportersOrkun S Soyer
Department of Chemistry, University of Michigan, Ann Arbor, MI 48109, USA
J Mol Biol 339:227-42. 2004..Based on this application we present testable hypotheses regarding the mechanism of action of these proteins...
Adaptive dynamics with a single two-state proteinAttila Csikasz-Nagy
Microsoft Research University of Trento Centre for Computational and Systems Biology, Piazza Manci 17, Povo Trento, Italy
J R Soc Interface 5:S41-7. 2008..The analysis of coupled BioNetUnits will show how the presented dynamics at single unit will change upon increased system complexity and how such systems would mediate biological functions...
Depicting a protein's two faces: GPCR classification by phylogenetic tree-based HMMsBin Qian
Biophysics Research Division, University of Michigan, Ann Arbor, MI 48105, USA
FEBS Lett 554:95-9. 2003..In this study we used the method to generate common features of G protein-coupled receptors (GPCRs). The profile generated by T-HMM gives high accuracy in GPCR function classification, both by ligand and by coupled G protein...
Dimerization in aminergic G-protein-coupled receptors: application of a hidden-site class model of evolutionOrkun S Soyer
Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA
Biochemistry 42:14522-31. 2003..On the basis of these findings, we propose an experimentally testable dimerization mechanism, involving interactions among different combinations of these helices in different families of aminergic GPCRs...
Probing conformational changes in neurotransmitter transporters: a structural contextNaomi R Goldberg
Center for Molecular Recognition, Columbia University, P and S 11-401, Box 7, 630 West 168th Street, New York, NY 10032, USA
Eur J Pharmacol 479:3-12. 2003....
Evolution of taxis responses in virtual bacteria: non-adaptive dynamicsRichard A Goldstein
Mathematical Biology, National Institute for Medical Research, London, United Kingdom
PLoS Comput Biol 4:e1000084. 2008....
