I-O stability and persistence analysis of open chemical reaction networks
David
Angeli
(Imperial College London)
Abstract:
Despite their non-linearity and complexity, chemical reaction networks
arising in biological systems exhibit remarkable robustness features which are largely unexpected
and generally not understood from a theoretical point of view. The aim of this
talk is to describe some attempts by the speaker and coworkers in developing qualitative tools for
understanding the dynamics of potentially complicated reaction networks. Most methods are
purely topological in nature and only rely on graph theoretical descriptions in order to derive
general statements as far as the resulting dynamical behaviour of the network.
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Synchronicity in nature's networks: unraveling the design and inspiration for engineering
Frank
Doyle
(University of California Santa Barbara)
Abstract:
The generation of highly robust rhythms from the synchronization of
large numbers of oscillators is is a recurring theme in biology. Of
particular interest in this talk is the exquisite synchrony achieved in
circadian oscillators in the brain, arising from a population of
"sloppy" cellular timekeepers that are linked by local signalling cues.
The details of the coupling mechanism will be presented, with an
emphasis on phase metrics for modeling and analysis. Extensions of this
work for other biological systems, including coral reproduction, will be
outlined. These insights are also used to suggest novel strategies for
engineered networks.
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Probing transcription factor kinetics at the level of single molecules
Johan Elf
(Uppsala University)
Abstract:
DNA binding proteins can speed up their rate of binding specific sites
by using a combination of sliding along the DNA contour and free
diffusion though the cytoplasm. We have studied this process in
living cells using single molecule microscopy. The results are
compared to a new theoretical model for the search kinetics in living
cells.
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Structure ranking and system Identification for non-linear biochemical process
models: inferring the structure of the ERK pathway via Bayes factors
Mark Girolami
(University of Glasgow)
Abstract:
Mechanistic mathematical models of biochemical systems are
important tools in the study of cellular processes. Such models make
explicit current assumptions about the structure and dynamics of the systems
of interest whilst statistical methodology enables their evaluation against
experimental observation. This talk will present Bayesian statistical
methods for system identification, that is, for the estimation of unmeasured
parameters and the dynamics of unobserved species in biochemical models
described by systems of nonlinear Ordinary Differential Equations (ODE). In
addition a means of objectively ranking a number of plausible mathematical
models based on their evidential support as assessed by Bayes factors will
be presented. A large scale study of the Extra-Cellular Regulated Kinase
(ERK) pathway will be discussed where recent Small Interfering RNA (siRNA)
experimental validation of the structural predictions made using the
computed Bayes factors is presented.
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Modeling circadian rhythms : From molecular mechanism to physiological disorders
Albert
Goldbeter
(Université Libre de Bruxelles)
Abstract:
Computational models of increasing complexity have been proposed for circadian rhythms which occur with a period close to 24h as a result of gene regulation in Drosophila and mammals. The models show how circadian oscillations occur spontaneously in constant environmental conditions, e.g., continuous darkness, and account for entrainment of the circadian clock by the light-dark cycle and for phase shifts induced by light pulses. Computational models further indicate how multiple sources of oscillatory behavior may originate from interlocked regulatory loops in the genetic network underlying circadian rhythms. Stochastic versions of the models indicate the domain of validity of deterministic approaches. A computational model for the mammalian circadian clock allows us to examine the dynamical bases of circadian clock-related physiological disorders in humans. Entrainment by the light-dark cycle with a phase advance or a phase delay is associated with the Familial advanced sleep phase syndrome (FASPS) or the Delayed sleep phase syndrome (DSPS), respectively. Lack of entrainment corresponding to the occurrence of quasiperiodic oscillations can be associated with the non-24h sleep-wake syndrome. It is important to clarify the conditions for entrainment and for its failure because dysfunctions of the circadian clock may lead to physiological disorders, which pertain not only to the sleep-wake cycle but also to mood and cancer.
References :
Leloup J-C, Goldbeter A. 2003. Toward a detailed computational model for the
mammalian circadian clock. Proc Natl Acad Sci USA 100:7051-7056.
Leloup J-C, Goldbeter A. 2004. Modeling the mammalian circadian clock: Sensitivity
analysis and multiplicity of oscillatory mechanisms. J Theor Biol 230:541-562.
Leloup J-C, Goldbeter A. 2008. Modeling the circadian clock : From molecular mechanism to physiological disorders. BioEssays, in press.
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Developments in Computational Physiology
Peter Hunter
(Bioengineering Institute, Auckland)
Abstract:
The Physiome Project of the International Union of Physiological Sciences (IUPS) is attempting to provide a comprehensive framework for modelling the human body using computational methods which can incorporate the biochemistry, biophysics and anatomy of cells, tissues and organs. A major goal of the project is to use computational modelling to analyse integrative biological function in terms of underlying structure and molecular mechanisms. A newly formed EU Network of Excellence for the Virtual Physiological Human (VPH) is also contributing and, in particular, addressing clinical applications of the project.
To facilitate model reuse among researchers in computational physiology, two XML markup languages for encoding biological models, CellML (www.cellml.org) & FieldML (www.fieldml.org), are being developed. CellML deals with models of so-called 'lumped parameter' systems, where spatial effects are averaged, and typically involves systems of ordinary differential equations and algebraic equations. FieldML addresses the spatial variations in cell or tissue properties where the models typically rely on partial differential equations. The two standards can be used together. These languages, which define the structure of a model, the mathematical equations and the associated metadata, enable (i) automated checking to ensure consistency of physical units used in the model equations, (ii) models developed by different groups to be combined using commonly agreed ontological terms within the metadata, (iii) models to be modularized and used in libraries to make it easier to create complex models by importing simpler ones. Model repositories based on these standards and implementing a wide variety of models from peer-reviewed publications have been developed (www.cellml.org/models) and open source software tools for creating, visualizing and executing these models are currently available (www.cellml.org/tools) and under continuous development.
The application of this framework to modeling the heart and other organs will also be presented.
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Towards detecting targets in static and dynamic biochemical networks
Edda Klipp
(MPI for Molecular Genetics, Berlin)
Abstract:
Theory-based prediction of targets for drugs and directed intervention in biological networks is still in its infancy. This holds both for diseases that are caused by intracellular changes (such as genetic disorders, cancer) as well as for diseases that are induced by parasites. Based on established and carefully tested models of dynamic cellular processes, we strive to develop a theoretical prediction of drug targets and for the assessment of the effect of a drug application. Moreover, we discuss a search schema for combinations of drug targets that together allow for a more effective treatment than single treatments. Specifically, we will also test different types of interactions (inhibition and activation) of the drugs with their targets [1].
[1] Gerber, S., et al., Drug-efficacy depends on the inhibitor type and the target position in a metabolic network--a systematic study. J Theor Biol, 2008. 252(3): p. 442-55.
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