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Biological pathway and systems analysis

Biological pathway and systems analysis. An introduction. Biomedicine ‘ after the human genome ’. Patient. Molecular basis of disease. Current disease models. Molecular building blocks.

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Biological pathway and systems analysis

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  1. Biological pathway and systems analysis An introduction

  2. Biomedicine ‘after the human genome’ • Patient Molecular basis of disease Current disease models Molecular building blocks very data-rich about genes, genome organisation, proteins, biochemical function of individual biomolecules genes proteins

  3. Patient Disease manifestation in organs, tissues, cells Molecular organisation Physiology Clinical data Molecular basis of disease ? Current disease models Molecular building blocks genes proteins

  4. Patient physiology, clinical data Disease manifestation in organs, tissues, cells Molecular organisation Complex disease models tissues organs Computational modelling Molecular building blocks genes proteins

  5. Global approaches: Systems Biology Perturbation Living cell Dynamic response Bioinformatics Mathematical modelling Simulation • Basic principles • Applied uses, e.g. drug design cell network modelling “Virtual cell”

  6. Dynamic biochemistry • Biomolecular interactions • Protein-ligand interactions • Metabolism and signal transduction • Databases and analysis tools • Metabolic and signalling simulation • Metabolic databases and simulation • Dynamic models of cell signalling

  7. Dynamic Pathway Models • Forefront of the field of systems biology • Main types Metabolic networks Gene networks Signal transduction networks • Two types of formalism appearing in the literature: • data mining  e.g. genome expression at gene or protein level  contribute to conceptualisations of pathways • simulations of established conceptualisations

  8. Dynamic models of cell signalling …from pathway interaction and molecular data Erk1/Erk2 Mapk Signaling pathway …to dynamic models of pathway function Schoeberl et al., 2002

  9. Simulations: Dynamic Pathway Models Epidermal growth factor (EGF) pathway • These have recently come to the forefront due to emergence of high-throughput technologies. • Composed of theorised/ validated pathways with kinetic data attached to every biochemical reaction - this enables one to simulate the change in concentrations of the components of the pathway over time given initial parameters. • These concentrations underlie cell behaviour. Schoeberl et al (2002) Nat. Biotech 20: 370

  10. The epidermal growth factor receptor (EGFR) pathway

  11. The effect of the number of active EGFR molecules on ERK activation EGFR 500,000 active receptors PLC Ras PI3K PKC MAPK PKB/Akt 50,000 active receptors = Inhibition by one order of magnitude TFs Functional targets ERK CELL GROWTH AND PROLIFERATION Schoeberl et al., 2002, Nat. Biotech. 20: 370

  12. The effect of active EGFR number on ERK activation 500,000 active receptors 50,000 active receptors Can this be achieved by receptor inactivation alone?

  13. The effect of active EGFR number on ERK activation 50,000 active receptors with normal levels of ERK or ERK overexpression and cross-activation

  14. Hunter and Borg (2003)

  15. Virtual Physiological Human Simulation of complex models of cells, tissues and organs www.vph-noe.eu • Heart modelling: 40+ years of mathematical modeling of electrophysiology and tissue mechanics • New models integrate molecular mechanisms and large-scale gene expression profiles

  16. Multi-level modelling integration across scales through computational modelling patient organ Anatomy and integrative function, electrical dynamics Vessels, circulatory flow, exchanges, energy metabolism Cell models, ion fluxes, action potential, molecules, functional genomics cell

  17. Spatial distribution of key proteins • Transmural expression differences of an ion channel protein leads to different action potential profiles at the epicardium, midwall and endocardium • Arrhythmias Hunter et al (2005) Mechanisms of Ageing and Development 126:187–192.

  18. Virtual Physiological Human Project www.vph-noe.eu/ The Virtual Physiological Human https://www.youtube.com/watch?v=CM76-mS84Xs

  19. The hallmarks of systems biology • formulate a general or specific question • define the components of a biological system • collect previous relevant datasets • integrate them to formulate an initial model of the system • generate testable predictions and hypotheses • systematically perturb the components of the system experimentally or through simulation • study the results • compare the responses observed to those predicted by the model • refine the model so that its predictions fit best to the experimental observations • conceive and test new experimental perturbations to distinguish between the multiple competing hypotheses • iterate the process until a suitable response to the initial question is obtained

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