I Systems Microbiology(13 Lectures 7hece∥ as a we∥}- stirred boc/ nem/ca/ reactor Introduction 2 Chemical kinetics, Equilibrium binding, cooperativity L3 Lambda phage L4 Stability analysis L5-6 Genetic switches L7-9 E coli chemotaxis L10-11 Genetic oscillators L12-13 Stochastic chemical kinetics
I Systems Microbiology (13 Lectures) ‘The cell as a well-stirred biochemical reactor’ L1 Introduction L2 Chemical kinetics, Equilibrium binding, cooperativity L3 Lambda phage L4 Stability analysis L5-6 Genetic switches L7-9 E. coli chemotaxis L10-11 Genetic oscillators L12-13 Stochastic chemical kinetics 1
II Systems Cell Biology(9 Lectures) The cell as a compartmentalized system with concentration gradients L15 Diffusion, Fick's equations, boundary and initial conditions L16-17 Local excitation, global inhibition theory L18-19 Models for eukaryotic gradient sensing L20-21 Center finding algorithms L22-23 Modeling cytoskeleton dynamics
II Systems Cell Biology (9 Lectures) ‘The cell as a compartmentalized system with concentration gradients’ L15 Diffusion, Fic k’s equations, boundary and initial conditions L16-17 Local excitation, global inhibition theory L18-19 Models for eukaryotic gradient sensing L20-21 Center finding algorithms L22-23 Modeling cytoskeleton dynamics 2
Ill Systems Developmental Biology(2 Lectures The cell in a social context communicating with neighboring ce∥s 23 Quorum sensing L25 Drosophila development
III Systems Developmental Biology (2 Lectures) ‘The cell in a social context communicating with neighboring cells’ L23 Quorum sensing L25 Drosophila development 3
Main take home messages from this course 1. translate the biology into a quantitative model given the biology set up the coupled differential equations that capture the essence of the biological phenomena (not trivial since 4 papers came up with a different model given the same biological phenomenon which assumptions to make is critical) 2. analysis of the system of differential equations stability analysis(both in space and time) 3. interpretation of the mathematical analysis, what are the biological conclusions e.g. if the imaginary part of the eigenvalue is non zero, what does this mean for the underlying biology? 4. develop a taste for the potential of these systems approaches for biological problems that you may encounter in the future
Main take home messages from this course: 4 1. translate the biology into a quantitative model: given the biology set up the coupled differential equations that capture the essence of the biological phenomena (not trivial since 4 papers came up with a different model given the same biological phenomenon, which assumptions to make is critical) 2. analysis of the system of differential equations stability analysis (both in space and time) 3. interpretation of the mathematical analysis, what are the biological conclusions ? e.g. if the imaginary part of the eigenvalue is non zero, what does this mean for the underlying biology? 4. develop a taste for the potential of these systems approaches for biological problems that you may encounter in the future
Developmental Systems Biology Building an organism starting from a single cell Introducing Drosophila melanogaster (or the fruitfly) Great book: The making of the flyby Peter lawrence
Developmental Systems Biology ‘Building an organism starting from a single cell’ Introducing: Drosophila melanogaster (or the fruitfly) Great book: ‘The making of the fly’ by Peter Lawrence 5