Systems Biology

Introduction to Systems Biology. The importance and history of systems biology. Laws of systems biology. Dynamic behavious of biological systems and the methods for its analysis. Experimental methids for aquiring the data used in systems biology. Tools and methods of system biology. Data and model formats, visualization. Perspectives of systems biology. After the completion of this course, students will be able to: understand basic ideas, tools and applications of systems biology in biology, biotechnology and medicine.

Objectives, meaning, history, laws of systems biology. Dynamic behavior of biological systems, its analysis methods.

Molecular Biology, Bionanotechnology and Biomodeling, Comprehensive Analysis of Biological Systems

1. Introduction. Object of Systems Biology. Principles and Laws of Systems Biology: Similarities and Discrepancies Between the Laws of Systems Biology and Physics. Research Methods of Systems Biology: from Separation to Integration, from Molecules to Networks. 2. History of Systems Biology. 3. Kinetic Behaviour of Biological Systems, Methods of its Analysis. Models of biological systems: from simple chemical reactions to complex biological systems. Point and Spatially Distributed Systems; Deterministic and Stochastic Models (Markov Chains, Microscopic, Mezoscopic, and Macroscopic Models, etc.); Methods of the Description of the Behaviour of Biological Systems by Differential Equations. Time-Scale Hierarchy in Biological Systems. 4. Qualitative Analysis of the Biological Systems Described by Differential Equations. Stability, Stationary State, Bifurcation. Phase Plane and Phase Trajectories, Method of Isoclines, Singular Points. Noise and Perturbation of Biological Systems and Their Impact on System Stability. Noise in Enzymatic Systems. 5. Examples of the analysis of the kinetic behavior of biological systems: autocatalytic chemical reaction, simple and complex enzymatic reactions, Michaelis-Menten equation, bi- and multistable trigger systems, nonlinear systems, interaction of populations (Volterra-Lotka and other models), mesoscopic kinetics of protein synthesis, deterministic chaos. 6. Non-equilibrium Thermodynamics. The Onsager Relations. Prigogine’s Theorem. 7. Static Network Models: Interactions Graphs, Dependencies among Network Components, Network Motifs, Analysis of Static Networks. 8. Primary Sources and Acquisition Methods of the Data Used in Systems Biology: Classic Methods, Microarray, Microfluidic Systems, Omics Analysis (Genomics, Proteomics, Metabolomics, etc), etc. 9. Systems biology databases: reaction kinetics, metabolic pathways, signal transduction, nucleic acids, proteins, and models (BRENDA, BIND, BioCarta, SigPath, IntAct, GRID, CSB.DB, CellCircuits, BioModels, NCBI, etc.). 10. Systems biology tools: hardware and software (from CAIN to VCELL, SimBiology, METATOOL, CellDesigner, SBW, etc.), data models and formats (XML, SBML, CellML, etc.), analysis of algorithms, visualization (Cytoscape, Navigator, Osprey, et al.), etc. Cytoscape: open- source platform for analysis and visualization of complex networks. CELLWARE – the first web tool for modeling and simulation of biological systems. Systems Biology Workbench (SBW), its possibilities. Electronic cell system E-Cell - software for the simulation of a whole cell. Current E-Cell opportunities: dynamic simulation of in vitro multi-enzyme and cell metabolism systems, modeling of organelles, the application of the analysis of pathological states. 11. Application of the principles of systems biology for the analysis of biological systems (1): analysis of gene regulation and metabolic networks, signal transduction pathways; networks of protein interactions. Integration of metabolic and signaling networks. 12. Application of the principles of systems biology for the analysis of biological systems (2): analysis of the cell cycle, cell development, apoptosis. Systems biology of stem cells. 13. Application of the principles of systems biology in medicine (forecast of disease-related genes by using metabolic networks, disease-related subnets, personalized medicine, the whole body pharmacokinetic modeling (PK-Sim ), the virtual patient, etc.) and bio-pharmacy (application of metabolic networks for the search of selective targets for drugs, simulation of the response of a whole human body to the treatment (PhysioLab), etc. ) . 14. Application of the the principles of systems biology in biotechnology (improvement of the properties of microorganisms, optimization of biotechnological processes, etc.), toxicology, neuroscience, etc. 15. Scientific and technological challenges of systems biology, improvements required. Systems biology perspective (synthetic biology, virtual/electronic cells, organs, humans, etc.). Practical works 1. Introduction to CellDesigner. Basic Features. 2. Modeling of Chemical Reactions with CellDesigner. 3. CellDesigner: Modeling and Analysis of the Reaction of Decomposition of Hydrogen Peroxide. 4. CellDesigner: Creation and Analysis of Mathematical Rules in Models. 5. CellDesigner: Modeling and Analysis of the Circadian Clock Model. 6. CellDesigner: Connection to External Databases of Models 7. CellDesigner: Connection to External Databases 8. Introduction to Systems Biology Workbench (SBW) 9. SBW: Basic Features and Tools of JDesigner. 10. SBW: Creation and Analysis of the Model of Brusellator with JDesigner 11. Virtual Cell: Basic Features and Tools. 12. Virtual Cell: Creation and Analysis of the Model of Water Transport through the Membrane 13. Cytoscape: Basic Features 14. Cytoscape: Network Visualization and Analysis

Students who have completed the course will gain knowledge about: • goals, significance, history of origin and development of systems biology, principles and laws of systems biology, research methods. • the dynamic behavior of biological systems and its analysis methods, models used to describe simple reactions and complex biological systems; • qualitative analysis of biological systems described by differential equations, noise and perturbations in biological systems, their influence on system stability; specific examples of the kinetic behavior of biological systems; • primary sources of data used in systems biology and classical and new methods of acquisition; databases; • systems biology tools (hardware and software, data and model formats, analysis algorithms, visualization); • application of the principles of systems biology to the analysis of biological systems, medicine, biopharmacy, biotechnology, toxicology, neuroscience. • scientific and technological challenges of systems biology, perspectives of systems biology. will be able to: • understand the basic principles and laws of systems biology; • to create simple models describing kinetic and complex biological systems and to analyze their dynamic behavior; • describe the tools used in systems biology; • individual use of databases used in systems biology and use them for various purposes in systems biology; • construct, analyze and visualize complex metabolic and other networks; • to model the metabolism of an individual organ or cell; • to use systems biology methods to analyze biological systems, optimize biotechnological processes, solve pharmacological and medical problems.