Table of ContentsGene Regulation Networks - a Finite State Linear ModelGene networks - what does it mean to understand them? Modelling approach Simulation and reverse engineering of gene networks Existing models for gene networks Boolean network based models Differential equation based models Disadvantages of pure models Hybrid models Discrete vs. continuous behaviours A finite state linear model for gene networks - assumptions Environment: Substance binding sites PPT Slide A gene Gi: A gene Gi: A gene Gi: A gene network A gene network in action A gene network in action A three state binding site Multistate generalisation A multistate gene: PPT Slide Stochastic generalisation Concentration change graph Measurements that we can make (by array experiments) The reverse engineering problem: Theorem Step one: PPT Slide Step two In practice Reverse engineering in the strict sense Future work PPT Slide Acknoledgements |
Author: Alvis Brazma
Email: brazma@ebi.ac.uk Home Page: http://www.ebi.ac.uk/~brazma |