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

 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

 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

 Simulation application – live at uj.krakow.pl:8080/nfs/ 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