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The Context of Systems Biology

The Context of Systems Biology. Michele Griffa Dept. of Physics, Polytechnic of Torino michele.griffa@polito.it. The Role of Mathematical Modeling and Numerical Simulation in the Systems Biology Era Workshop Bioindustry Park of Canavese, Colleretto Giacosa February 28 th , 2006.

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The Context of Systems Biology

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  1. The Context of Systems Biology Michele Griffa Dept. of Physics, Polytechnic of Torino michele.griffa@polito.it The Role of Mathematical Modeling and Numerical Simulation in the Systems Biology Era Workshop Bioindustry Park of Canavese, Colleretto Giacosa February 28th, 2006

  2. Systems Biology: history of a grand challenge since ‘910s since ‘950s 2000 t Institute for Systems Biology, Seattle (www.systemsbiology.org) Leroy Hood Concept of Homeostasys (Cannon) Predator- Prey Dynamics (Volterra/Lotka) General Systems Theory (von Bertalanffy, 1967) Biological Cybernetics (Wiener/Rosenbluth) Automata Theory (von Neumann) Compartmental models in Physiology Biochemical oscillators “The HGP has given us a parts list. The next step is to capture the information from all the elements in a biological system: DNA, proteins, cells, tissues and organs, and then create new mathematical models that will represent the relationships between them” The Economist Technology Quaterly, september 17-23 2005 system-level understanding grounded in molecular-level one function and dynamics understanding of a whole biosystem prediction and control

  3. Systems Biology: history of a grand challenge 1990s: a leap forward t Post Genomic Era theory, modelling, computational power (hardware, algorithms) microtechs, total analysis-on-one device high throughput tools developed for genomes sequencing databases, WWW access and data mining 1 gene 1 protein Systems Biology approach needed ! gene regulatory networks transcriptional pathways metabolic pathways networks paradigms

  4. Systems Biology: goals Biosystems structure: • components • modules that implement functions • interplay between modules, relationships between components networks of gene interactions biochemical pathways mechanisms through which such interactions modulate physical properties of intracellular and multicellular structures control of the system  robustness (evolutionary) design: how to construct or modify biosystems having desired properties whole-biosystem dynamics: how a whole-system behaves over time under various (boundary) conditions

  5. Multi-Scale Modeling of the Heart,from Genes to Cells to the Whole-Organ:an example of Systems Biology-like result 1952: Hodgkin/Huxley’s model, study of the dynamical behaviour of the voltage dependent conductivity of a nerve cell membrane for Na+ and K+ ions, prediction of the dynamics of action potential and of axon conduction in giant squibb. electrophysiological activity of miocytes (oscillators models) emergence of synchronization in sets of coupled non-linear oscillators (pacemakers cell population dynamics, Winfree, 1980s) genetic mutations, protein expression and cardiac sodium channel dynamic behaviour (Clancy, Rudy, 1999) propagation of action potential wavefield in excitable media (incorporation of cellular models into whole-organ ones) mechanical-electrical feedback (how the contraction of the heart influences its electrical conduction properties) blood fluid dynamics around cardiac valves surfaces (immerse boundary methods for the solution of PDEs problems involving dynamic fluid-structure interaction, McQueen/Peskin, 1980s)

  6. Multi-Scale Modeling of the Heart,from Genes to Cells to the Whole-Organ Spread of the electrical activation potential wavefield in an anatomically detailed cardiac model (P. Kohl et al., Philos. Trans. R. Soc. London Ser. A 358, 579, 2000) red: activation potential wavefront; blue: endocardial surface Transmural pressure on coronary vessels from the myocardial stress (dark blue=0 press., red=peak press.) end-diastole early systole late systole (N.P. Smith, G.S. Kassab, Philos. Trans. R. Soc. London Ser. A 359, 1315, 2001)

  7. Systems Biology: a knowledge-management goal ! Integration and Scaling of Knowledge, Information, Data, Models, Simulation Tools: Integrative Biology ! large-scale measurements collection large-scale data/knowledge sharing modeling and simulation • KEGG (www.genome.ad.jp) • STKE (www.stke.org) • Alliance for Cellular Signaling (www.signaling-gateway.org) • BioCyc (www.biocyc.org) • BIND (www.bind.ca/Action?pg=0) SBML (www.sbml.org) CellML (www.cellml.org) BioUML (www.biouml.org) BioSpice (https://community.biospice.org) XML-based computer readable model definition languages; toolboxes for analysis, synthesis and simulation; R-DBMS, WWW data and text mining Semantic Web (XML-enabled techs)

  8. The Context of Systems Biology Michele Griffa Dept. of Physics, Polytechnic of Torino michele.griffa@polito.it The Role of Mathematical Modeling and Numerical Simulation in the Systems Biology Era Workshop Bioindustry Park of Canavese, Colleretto Giacosa February 28th, 2006

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