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Published byChandler Errett Modified over 9 years ago
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Negative feedback based organized systems simulations EUROPEAN UNION EUROPEAN REGIONAL DEVELOPMENT FUND The work was co-funded by the European Regional Development Fund as part of the Innovative Economy program. Jakub Wach 3, Marian Bubak 1,3, Leszek Konieczny 2, Irena Roterman-Konieczna 2 1 AGH University of Science and Technology, Department of Computer Science, Kraków, Poland 2 Jagiellonian University, Department of Bioinformatics and Telemedicine, Kraków, Poland 3 Academic Computer Centre Cyfronet AGH, Kraków, Poland
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Biosystem = in general, anything that is alive Mulitple levels – from a single enzyme to whole organism Simulations of biosystems New drugs development New treatments – affecting multiple parts of an organism Discovery of emergent properties of bio systems Existing simulation methods Various attempts – precise or statistical Issues Loosing details – missing „big picture” (statistical) Too complex to model a real organism (precise) Current top notch Stanford cell model is 40x less complex than a single human cell ! Problem definition
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Biosystems are thermodynamically open and need to self- regulate Create a biosystem out of simplest regulator – negative feedback inhibition system (NFIS) L. Konieczny, I. Roterman, P. Spolnik : “Systems biology”, 2014 Model biosystem as a functional proteome NFIS – building block Effector Delivers a product Output regulated by Receptor Receptor Delivers signal regulating Effector Signal output is regulated by product level Proposed solution
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Simulation application – live at http://crick.cm- uj.krakow.pl:8080/nfs/ http://crick.cm- uj.krakow.pl:8080/nfs/ Provides GUI for definition and manipulation of structure and parameters of a bio system Simulation – results and future Complex systems simulation – lots of data for analysis Future - workflow application to automate simulation and analysis
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