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Systems Biology @ Hamilton Institute ::: Seminars
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Forthcoming seminars & events

Brief talks

Past seminars

Past events

Forthcoming seminars and events
Nov 23, 2011 A stochastic T-cell response criterion
  Professor Carmen Molina-Paris, University of Leeds

T-cells sense their environment by means of T-cell receptors (TCRs) on their surface. A T-cell expresses about 30,000 copies of a unique (clonotypic) TCR, whose ligands are complexes composed of a peptide bound to an MHC molecule (pMHC). In vivo, TCR ligands are expressed on the surface of antigen-presenting cells (APCs). In the thymus a variety of professional APCs will subject immature T-cells (or thymocytes) to a "double test" by displaying a wide range of pMHC complexes, with peptides derived from household proteins (self-peptides). The stochastic nature of gene rearrangements implies that some TCRs will not be able to recognise a self-pMHC ligand (TCRs that are not functional) and that others will recognise it far too well, and thus would give rise to mature T-cells with the potential to generate autoimmune responses. Thus, the need for a double test that will check the functionality of a thymocyte(positive selection) and its state of tolerance, so that it does not recognise self-pMHC complexes with high affinities (negative selection). This thymic selection process only allows 2-5% of thymocytes to become mature T-cells.We have made use of mathematical modelling to address the following issues: (1) the thymic affinity threshold hypothesis proposed by Palmer and Naeher (Nature Reviews Immunology, 2009) and (2) time is precious for T-cells, so what do TCRs sense (i) equilibrium properties or (ii) stochastic events. We have made use of data from Palmer's group (The Journal of Experimental Medicine, 2007) to compare the equilibrium versus the stochastic hypotheses. Our results indicate that the stochastic hypothesis ties in better with the existing immunological evidence and provides support to the affinity threshold hypothesis. The stochastic model has also been applied to recent two-dimensional binding data by Huang et al. (Nature 2010) and sheds light into 2d versus 3d binding kinetics and T-cell responses.




Past seminars
Feb 23, 2011 Programming stem cells: modeling stem cell dynamics and organ development
  Dr Yaakov Setty, Weizmann Institute, Israel.

In recent years, we have used software engineering tools to develop reactive models to simulate and analyze the development of organs. The modeled systems embody highly complex and dynamic processes, by which a set of precursor stem cells proliferate, differentiate and move, to form a functioning tissue. Three organs from diverse evolutionary organisms have been thus modeled: the mouse pancreas, the C. elegans gonad, and partial rodent brain development. Analysis and execution of the models provided dynamic representation of the development, anticipated known experimental results and proposed novel testable predictions. In my talk, I will l discuss challenges, goals and achievement in this direction in science.


Dec 15, 2010 Event-Driven Automation in Laser-Scanning Microscopy Applied to Live Cell Imaging
  Dr Jakub Wenus, Systems Biology, Hamilton Institute, NUIM

Microscopy of living cells is heavily employed in biomedicine to understand the mechanisms of disease progression and to develop novel pharmaceuticals. In particular, confocal microscopy which relies on laser-based excitation of fluorescent cellular biomarkers is frequently used for understanding molecular actions of therapeutic drugs to abnormal cells. However, prolonged exposure to highly energetic laser radiation often leads to light induced cell death before any spontaneous effects can occur – an effect known as phototoxicity. To address this problem we have developed an automated live-cell imaging system ALISSA which employs online image processing and analysis to automatically detect biological events and then trigger appropriate changes in the image acquisition settings. This way we minimize the photo-toxicity, obtain higher quality of the imaging data and minimize direct user involvement by introducing more automation to the whole experimental process. So far, ALISSA has been used in studies on cancer cells and neurons at the Royal College of Surgeons in Ireland and it is currently under development aimed towards applications in commercial high content screening systems.


Jun 1, 2010 How Does the Brain Go from Sound to Meaning?
  Steven Greenberg, Silicon Speech
  Contemporary models of speech recognition by humans and machines are difficult to reconcile with many properties of spoken language. Pronunciation variation, robustness to acoustic interference, categorical perception, and lexical access are among the (many) phenomena the "standard framework" fails to explain. This presentation describes a new theoretical formulation, using hierarchical oscillatory networks (Hi- O Nets), that relates auditory speech processing with other sensory (e.g., vision) and cognitive (e.g., memory) data streams. Within the Hi-O framework, signal-parsing and pattern-matching are crucial stages in going from sound to meaning. They depend on the structured interaction of oscillatory neural activity across a broad range of time constants characteristic of speech (20-2000 ms). A multi-time-scale, hierarchical oscillatory framework can account for many phenomena in spoken language, including (1) the ability to understand speech in background noise and other forms of acoustic interference, (2) the effect of sentential and semantic context on speech intelligibility, and (3) the perceptual invariance of highly variable and dynamic acoustic signals. Hi-O Nets will be illustrated and discussed with reference to both classic and more recent perceptual studies. Flyer.
April 8, 2010 Systems Analysis of Cellular Networks Under Uncertainty
  Professor Joerg Stelling, Dept. of Biosystems Science & Engineering, ETH Zurich.

For complex cellular networks, limited mechanistic knowledge,conflicting hypotheses, and relatively scarce experimental data hamper the development of mathematical models as systems analysis tools. The talk focuses on two approaches for dealing with this combination of complexity and uncertainty. They combine theory development and applications to specific biological examples. Firstly, network reaction stoichiometries are relatively well-characterized and therefore suitable starting points for pathway analysis. It allows one to investigate the space of a (metabolic) networkos feasible states. Applications are becoming possible for genomescale networks, and they range from investigating the effects of network perturbations to predicting cellular control features. Moreover, recent theory extensions connect the approach to systems dynamics, for instance, to identify key mechanisms in cellular decision processes. Secondly, and more mechanistically, we propose to cast hypotheses into a library of dynamic mathematical models, evaluate these against experimental observations, and design pivotal experiments to discriminate between alternatives. For TOR signaling in yeast, this strategy identified key control mechanisms that are quantitatively consistent with all available experimental data, and systematic extension of the approach to larger networks is a current challenge. Overall, the importance of network structures seems to outweigh the fine tuning of parameters. Structure-oriented analysis of biological systems, thus, provides challenging theory problems as well as broad perspectives for uncovering the organization and functionality of cellular networks. Flyer

Feb 10, 2010 Combining Pharmacology and Mutational Dynamics to Understand and Combat Drug Resistance in HIV
  Dr. Max von Kleist, Department of Mathematics and Computerscience, Freie Universität Berlin
  The cure for HIV remains to be found, even after 25 years of research. The use of highly active antiretroviral therapy (HAART) has led to a dramatic decline in morbidity associated with the infection. However, the virus develops drug resistance, thereby eliminating treatment options and putting the patient in risk of death. Up to now, the mechanisms of resistance development are poorly understood. A population of species (like HIV) can respond to a novel threat (drug treatment) by generating offspring with an adapted phenotype (drug resistance). During the first month of HAART, the concentration of virus in the blood is reduced by at least five orders of magnitude. This reduction of viral abundance is, however, not paralleled by a reduction in the probability to develop resistance. Stable, ongoing replication of HIV in compartments, which are not reflected by clinical measurements (HIV concentration in the blood), might explain this inconsistency. The reasons for insufficient drug penetration, and consequently -inhibition, can be elucidated by studying the pharmacology of antiviral drugs. While the two aspects, pharmacology and viral dynamics are often studied separately, we aim at combining them. To this end, we developed mathematical modeling approaches that enable to simultaneously consider the pharmacology of drugs, their distinct mechanism of action, viral dynamics and the ability of the virus to adapt to the pharmacological challenge. The mathematical models are constructed in a way that allows the use of various in vitro and in vivo data for parameterization. Consequently, the models can be used to study reasons for resistance emergence. Flyer.
Jan 29, 2010 Global sensitivity analysis of ODEs & a statistical study of mice sperm
  Dr. Andrea Weisse
  Global sensitivity analysis of ODEs & a statistical study of mice sperm? The talk is split into two parts. The first part contains the main results of my thesis, where I focused on ODEs subject to uncertain or variable parameter and initial values. Assuming that the initial uncertainty is characterized by a known probability density function (pdf), the final uncertainty can be characterized by solving a first-order PDE that describes the evolution of the pdf in time. The main outcome of this work is a numerical method for adaptive density propagation---adaptive both in temporal & spatial discretization---which can be used for global sensitivity analysis of ODEs. In the second part of the talk I present a statistical study from a project in collaboration with the developmental genetics group at the MPI for molecular genetics. The group studies molecular mechanisms during spermatogenesis that lead to non-Mendelian inheritance in mice. The current belief in genetics is that between sperm cells, developing in a common syncytium, gene products are exchanged via intercellular bridges. As a result, all sperm cells within one individual are phenotypically equivalent and thus have equal chances of fertilizing the ovum---the basic assumption for Mendelian genetics. In this study we could show that some genes, involved in sperm motility, can escape this mechanism and are actively retained within the cell. The resulting phenotypical difference contradicts the current dogma and provides an explanation for non-Mendelian inheritance.
Dec 9, 2009 A Phylogenetic Hidden Markov Model for Immune Epitope Discovery
  Prof. Cathal Seoighe, Dept. of Mathematics, NUI Galway
  We describe a phylogenetic model of protein-coding sequence evolution that includes environmental variables. We apply it to a set of viral sequences from individuals with known human leukocyte antigen (HLA) genotype and include parameters to model selective pressures affecting mutations within immunogenic (epitope) regions that facilitate viral evasion of immune responses. We combine this evolutionary model with a hidden Markov model to identify regions of the HIV-1 genome that evolve under immune pressure in the presence of specific HLA class I alleles and may therefore represent potential T cell epitopes. This phylogenetic hidden Markov model (phylo-HMM) provides a probabilistic framework that can be combined with sequence or structural information to enhance epitope prediction. Flyer.
July 15, 2009 Can't move to the rhythm? Inappropriate neuronal synchrony and oscillations in Parkinson's disease.
  Dr. Peter Magill, MRC Anatomical Neuropharmacology Unit, University of Oxford.
  The overall objective of the Magill Group’s research is to provide new insights into the functions and mechanisms of neuronal network activity in the basal ganglia, with a focus on elucidating how mutual interactions between these nuclei, as well as inputs from key extrinsic sources like the cerebral cortex and thalamus, orchestrate the activity patterns that are generated therein. Electrophysiological and anatomical techniques are used to dissect the normal and pathological (Parkinsonian) interactions of neurons within these circuits. This multidisciplinary approach, and the use of two complementary in vivo preparations, anaesthetised and freely-moving rodents, enables the group to elucidate the importance and substrates of neuronal network activity at several functional levels. Flyer.
June 17, 2009 A systems biology approach to apoptosis signalling
  Dr. Eric Bullinger, Institut Montefiore, Université de Liège, Belgium.
  Apoptosis is an important physiological process crucially involved in the development and homeostasis of multi-cellular organisms. Although the major signalling pathways leading from the extrinsic induction to the execution of apoptosis have been unravelled, a detailed mechanistic understanding of the complex underlying network and the signal crosstalk remains elusive. A systems biology approach allows to combine diverse data into mathematical models to perform predictive simulations and testing of quantitative and dynamical hypotheses. The modelling process furthermore reveals theoretical and computational challenges. Flyer.
June 10, 2009 How to understand the cell by breaking it - computational inference of cellular networks from gene perturbation screens
  Dr. Florian Markowetz, Cancer Research UK, Cambridge Research Institute.
May 6, 2009 Multivariate Time Series Analysis in Neurology
  Björn Schelter, Freiburg Center for Data Analysis and Modeling

Nowadays, data are recorded with increasing spatio as well as temporal resolution. This calls for new methods to analyze these data sets. Caused by the high spatio as well as temporal resolution of the recorded signals, inference of the causal network structure underlying them becomes feasible. In many applications a detailed analysis of these networks allows deeper insights into the normal functioning or malfunctioning of the system. In Neurology this helps to understand certain diseases like epilepsy or Parkinson's disease.

Novel concepts to analyze multivariate data consisting of both time series as well as point processes will be presented. By means of an application to tremor in Parkinson's disease, the abilities and limitations of these techniques are discussed.

Mar 12, 2009 Value of Pharmacokinetic and Pharmacodynamic Modelling for Tumour Patients
  Prof. Charlotte Kloft, Martin-Luther-Universität Halle-Wittenberg

In cancer chemotherapy, despite dose adaptation to body surface area for classical cytotoxic agents and some novel ‘targeted therapies’, the degree of interpatient variability in effects is large: Some patients fail to respond, whereas others experience unacceptable toxicity. Pharmacokinetic analysis of (sparse) concentration-time data in oncology have provided useful and sometimes crucial information during drug development and therapeutic use. However, only few (population) pharmacodynamic models have been presented, mostly focussing on myelosuppression as the most common, often dose- limiting toxicity. Myelosuppression, especially neutropenia makes patients highly susceptible to pathogens resulting in life-threatening infections or even death.

This presentation will focus on pharmacokinetic and pharmacodynamic modelling, especially mechanism-based population models, that may contribute to more rational drug development and optimal use of these drugs in tumour patients.

Mar 10, 2009 Model-Based Functional Brain Imaging and the Neurobiological Basis of Human Reinforcement-Learning
  John P. O'Doherty, Trinity College Institute of Neuroscience, Trinity College Dublin, Ireland.
Mar 4, 2009 Analysis of dynamical systems with steep sigmoidal response functions
  Prof. Erik Plathe, Norwegian Centre for Integrative Genomics

In models for gene regulation, the activity of a gene is regulated by the concentration of certain transcription factors. Frequently one assumes that the effect of the transcription factor (the response function) rises sharply from a low level to a saturation level around a threshold: i.e. its response function is sigmoidal or perhaps binary (a step function). Both cases are seen in experiments. If a gene is regulated by several transcription factors, Boolean-like functions determine their combined effect on the gene.

Gene regulatory models with step functions can be dealt with by means of a method devised by Filippov. After briefly sketching the idea behind this method, I will turn to models with steep sigmoidal response functions. The major problem is to analyse the behaviour when one or several variables are near a threshold. There the model becomes discontinuous in the limit when the sigmoids approach step functions.

I derive an equivalent set of equations which behave smoothly in these parts of phase space and which are much easier to analyse than the original equations. By investigating the limit when the sigmoids approach step functions, I will show how singular perturbation theory can be employed to analyse the behaviour of the model and compute solutions valid in the step function limit. These solutions are uniform approximations to the solutions for steep sigmoids. The limit solution could also be seen as an alternative to the Filippov definition of the solution to the same model with step functions instead of sigmoids. Flyer

Jan 28, 2009 Kinetic Modelling of Metabolism
  Prof. David Fell, Oxford Brookes University
  I will introduce the principles behind, and different approaches to, the building of mathematical models of metabolism. Then, focusing on kinetic models, I will deal with the issues of defining and parameterizing appropriate rate functions. Applications of kinetic modelling, and the analysis of kinetic models, will be illustrated with examples from bacterial threonine metabolism, plant carbohydrate metabolism and the mitochondrial tricarboxylic acid cycle. Similar approaches can be applied to the modelling of other cellular processes. Flyer.
Jan 21, 2009 Extracellular Potassium Dynamics and Epileptogenesis
  Maxim Bazhenov, University of California, Riverside
  Extracellular ion concentrations change as a function of neuronal activity and also represent important factors influencing the dynamic state of a population of neurons. In particular, relatively small changes in extracellular potassium concentration mediate substantial changes in neuronal excitability and intrinsic firing patterns. While experimental approaches are limited in their ability to shed light on the dynamic feedback interaction between ion concentration and neural activity, computational models and dynamic system theory provide powerful tools to study activity-dependent modulation of intrinsic excitability mediated by extracellular ion concentration dynamics.
Drawing on results obtained with biophysical network models of the thalamocortical system, I will discuss the potential role of extracellular potassium concentration dynamics in the generation of epileptoform activity in neocortical networks. Detailed bifurcation analysis of a model pyramidal cell revealed a bistability with hysteresis between two distinct firing modes (tonic firing and slow bursting) for mildly elevated extracellular potassium. In neocortical network models, this bistability gives rise to previously unexplained slow alternating epochs of fast runs and slow bursting as recorded in vivo during neocortical electrographic seizures in cats and in human patients with the Lennox-Gastaut syndrome. We conclude that extracellular potassium concentration dynamics may play an important role in the generation of seizures.
Jan 14, 2009 Modelling the synapse: from numbers to networks
  Eduardo Mendoza, Ludwig-Maximilian Universität, München.
  Recent studies have reinforced the important role of synaptic processes, in particular in enabling synaptic plasticity, for understanding brain function as well as neuropsychiatric diseases (e.g. [1], [2]). The talk will first review the evolution of synapse models from mere numerical constants ('weights') in early connectionist models to the emerging systems biological view of complex, dynamic networks. It will then discuss how the study of synaptic networks is contributing not only to understanding neuropsychiatric diseases but also how it could contribute to bringing together traditional computational neuroscience and the emerging systems neurobiology [3,4].
[1] L. Abbott, W.A. Regehr, Synaptic computation (2004), Nature 431.
[2] Kauer, J.A., Malenko, R.C. Synaptic plasticity and addiction (2007), Nature Reviews Neuroscience, Vol. 8, Nov 2007
[3] N. le Novere, The long journey to a Systems Biology of neuronal function (2007), BMC Systems Biology I: 28
[4] E. de Schutter, Why Are Computational Neuroscience and Systems Biology so separate? PLoS Computational Biology (2008), Vol 4, Issue 5

Dec 10, 2008 Exploring Multistability in Biochemical Networks
  Antonio A. Alonso, GEPRO, IIM-CSIC, Vigo, Spain
  The dynamics of biochemical networks such as regulatory or signalling pathways may entail qualitative changes in its behaviour as the values of their parameters, namely kinetic constants or enzyme concentrations are perturbed. These parameters are in fact responsible of a rich dynamic behaviour which in the form of multistability or oscillations, sustains functionality at the cell level.
From this perspective, it seems worth exploring periodicity, instability or any other qualitative features the system could exhibit for different ranges of parameter values. To that purpose, classical bifurcation techniques could be employed provided that the number of critical parameters remains small. Unfortunately this is not the case for most biochemical networks, where a large number of critical parameters might be involved.
In this seminar I would like to present some ideas and results we are working on to systematically detect and explore the regions in the space of parameters where different complex behaviour might appear. The approach has been built in the formalism of Chemical Reaction Network Theory as developed by Horn and Feinberg.
Interestingly, these regions -with their own characteristic behaviour- turn out to depend on a very small number of parameters closely related to the deficiency of the biochemical network under consideration. As it will be illustrated through some representative examples, the methodology can be also applied to compute the set of all possible reaction network parameters leading to multiple equilibria.
Nov 12, 2008 A systems approach to the modelling of visual hallucinations
  Richard Abadi, E.T.S. Walton Visitor
Sep 24, 2008 Spatial mapping of the Earth beneath the ocean - systems of a different kind
  Peter Simpkin, IKB Technology
  The idea of treating our planet as a system was first mentioned by Renaissance scientists as they looked for new models with which to describe the universe. This process continued through the centuries, until the book ‘Gaia: A New Look at Life on Earth’ by James Lovelock, introduced the public at large to the shocking fact that Earth was a limited resource with bio-systems that reacted to inputs from mankind – often in unattractive ways.
No group of researchers is more aware of the limited and special nature of the planet than marine biologists and geophysicists. They have known this for many decades and through marine biology and geology have traced the gradual impact of mankind. This talk will give an overview of this area taking the view of a marine geophysicist and instrumentation specialist who over a forty year career has designed, built and applied marine survey equipment. Drawing on experiences in most of our seas and oceans, but most notably of the Eastern Seaboard of North America, Dr Simpkin will describe the problems and successes of spatial mapping the Earth’s oceans. Flyer.
May 14th, 2008 An Integrative Computational Model of Colorectal Carcinogenesis
  Dr. Ingeborg M.M. van Leeuwen, University of Dundee, Scotland
  As part of the Integrative Biology project, we have formulated a multi-scale model to describe the processes involved in normal intestinal tissue renewal and colorectal cancer (CRC) development. At the subcellular level, deterministic continuum models characterise the behaviour of fundamental biochemical networks (i.e. cell-cycle control and Wnt signalling) in response to intra- and extra-cellular cues. The outcome of these models determines the regulation and co-ordination of cellular events (i.e. proliferation, differentiation, apoptosis, migration and adhesion) within the intestinal epithelium. Under aberrant conditions, loss of control can cause increased cell division and/or decreased cell differentiation and death. This can have serious implications for the maintenance of the integrity of the crypt, as the resulting proliferative excess and biomechanical stress can lead to crypt deformation, fission and eventual polyp formation. Our multi-scale approach enables us to investigate the impact of mutations commonly detected in CRCs, combine highly disparate data-sets, explore possible interactions between phenomena occurring at different levels of organisation and, in the future, test anti-cancer drugs on the system as a whole. Flyer.
Apr 16th, 2008 Dark Energy, Vacuum Fluctuations and Microscopic Irreversibility
  Prof. Michael C. Mackey, McGill University
  Modern ergodic theory of dynamical and semi-dynamical systems, combined with newer concepts from irreversible thermodynamics, have given new and surprising insights into the possible origins of irreversible behaviour. In this talk I will outline these in detail. I further hypothesize that one of the conclusions reached may be related to a possible connection between vacuum fluctuations (zero point energy) and the recently discovered dark energy driving the accelerated expansion of the universe. Flyer.
Apr 22nd, 2008 Optimization and Optimality in Systems Biology
  Prof. Julio Banga, CSIC Spanish Council for Scientific Research, Vigo, Spain
  Optimization is a key methodology in engineering. Since engineering approaches to systems biology are playing a significant rôle in the rapid evolution of systems biology, it is expected that mathematical optimization methods will contribute in a significant way to advances in systems biology. Similarly, it is also expected that optimality conditions will be useful to unravel the design principles of biological systems.
In this talk, I will highlight several topics where optimization has already made significant contributions. Examples will be given where optimization methods are used for topics ranging from model building and optimal experimental design to metabolic engineering and synthetic biology. Finally, several perspectives for future research are outlined. Flyer.
Apr 8th, 2008 Structural Modelling of the Whole Head for Electrical Impedance Imaging and Deep Brain Stimulation
  Prof. Richard Bayford, Middlesex University and Imperial College
  The use of deep brain stimulation (DBS) for clinical treatment for various neurological disorders, particularly movement disorders such as Parkinson's disease is on the increase. However, the mechanism by which this electrical stimulation acts on neuronal activity is unclear. Experimental in situ investigation of the mechanism of DBS in animal models or patients has clear limitations due to the multi-factorial nature. Our aim is to produce an accurate computational model to simulate the current flow produced by DBS. This will increase the understanding of the precise effects of the injected current on the surrounding neural tissue. It will also allow us to predict optimum dynamic injection and measurement protocols required to maximise the effects of DBS in a defined region of the brain. To address this problem we have adapted a bio imaging method known as electrical impedance tomography (EIT) for DBS by extending the forward problem to create models of the whole human head to simulate the dynamic electrical field distribution during deep brain stimulation. Flyer.
Feb 6th, 2008 Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism
  R. Fleming, NUIG & Visiting scholar, Palsson Systems Biology Research Group, UCSD, San Diego, USA
  In the modelling of biochemical networks at steady state, equations representing mass conservation, energy conservation, the second law of thermodynamics and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables.The reformulation is exact and amenable to large scale nonlinear numerical analysis using linear algebra, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic parameters in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that steady state fluxes are both thermodynamically and biochemically feasible. Preliminary numerical results are demonstrated for a genome scale E.coli model with ~1600 metabolites and ~2300 fluxes. Connections between the current approach and the mathematics of differential geometry and algebraic geometry are highlighted. Flyer.
Nov. 14th, 2007 Seeing more than meets the eye
  Richard Abadi, University of Manchester
  Making sense of what we see relies on both data driven (bottom-up) and hypothesis (top-down) processing. This latter stream uses internal models of the world and expectation to bring awareness and plausible meaning to seeing. On occasions, when direct analysis of the visual input becomes impaired by disease or trauma, higher order processing can compensate by perceptually completing the missing input, and, in cases of extensive visual loss, can also be responsible for the generation of visual hallucinations. The occurrence of these possibilities offer useful opportunities to explore and understand the neural underpinning of perception. This lecture will describe some of our laboratory and clinical studies to characterise these phenomena.Flyer
Oct. 3rd, 2007 Mathematical modelling of cell signalling pathways: a useful tool for data integration and validation of hypothesis
  Julio Vera, University of Rostock
  In recent years, the analysis of cell signalling systems through data-based models in ordinary differential equations (ODE) or other paradigms (e.g. stochastic models) has emerged as an invaluable tool to understand the underlying complexity of the protein interactions happening in cellular signal transduction. Compared with other biochemical systems, the modelling of cell signalling systems faces additional difficulties related to the challenges quantifying protein-protein processes but also to the lack of complete information about the topology of the considered network interactions. Since in most of the metabolic systems the complete network of interactions is (virtually) perfectly established, in cell signalling systems the real structure of the pathways is an open question to be elucidated either in parallel or through mathematical modelling based analysis.
In this context, the flexibility of kinetic models based on power-law equations with non-integer kinetic orders has been validated in the recent times as a tool to elucidate the structure of biochemical pathways via quantitative data based modelling. In addition, recent investigations suggest that this modelling framework could be a suitable tool for investigations on the structure and systemic properties of cell signalling pathways.
In this talk we discuss the use of power-law models (advantages and challenges) in biochemical systems. We also show how pre-existent biological knowledge and quantitative data can be integrated through mathematical modelling to validate hypothesis about the structure of signalling pathways. Flyer
Sep. 27th, 2007 Stochastic modelling of the immune response
  Ken Duffy and Vijay Subramanian, Hamilton Institute, NUIM
  During an adaptive immune response, lymphocytes proliferate for five to twenty cell divisions, then stop and die over a period of weeks. The recently proposed Cyton Model of lymphocyte proliferation provides a framework for studying this response. Experimental evidence indicates that the fate of individual cells is potentially highly variable. Thus the model assumes stochastic values for division and survival times for each cell in a responding population.
In the paper that proposed the Cyton Model, the mathematical analysis used a direct approach that enabled prediction of the mean immune response. Given the stochastic nature of the model a more refined analysis is needed to determine the likelihood that the typical response is close to the mean response. In this talk we present a more sophisticated stochastic analysis of the system by introducing a generalisation to the Bellman-Harris branching process. This enables us, for example, to determine the expected variability in the immune response, which arises due to its cell-level stochasticity.
We compare the predictions to experimentally observed lymphocyte population sizes from experiments. The important biological conclusion that immune response is typically robust and predictable despite the potential for great variability in the experience of each individual cell.
We will assume as little probabilistic knowledge of the audience as possible. Flyer
Aug. 28th, 2007 A Point-Based Algorithm for Multiple 3D Surface Alignment of Drug-Sized Molecules
  Daniel Baum, Zuse-Institut Berlin
  One important step in virtual drug design is the identification of new lead structures with respect to a pharmacological target molecule. The search for new lead structures is often done with the help of a pharmacophore, which carries the essential structural as well as physico-chemical properties that a molecule needs to have in order to bind to the target molecule. In the absence of the target molecule, such a pharmacophore can be established by comparison of a set of active compounds. To identify their common features, a multiple alignment of all or most of the active compounds is needed. Since the molecular shape plays a major role in the interaction between drug and target, an alignment algorithm aiming at the elucidation of a pharmacophore should consider the molecule's `outer shape', which can be approximated best by some kind of molecular surface.
This talk presents a new approach to molecular surface alignment which is based on a discrete representation of shape as well as physico-chemical properties using points. To distribute points regularly on a molecular surface w.r.t. a smoothly varying point density given on that surface, we developed a new point distribution method based on centroidal Voronoi tesselation. For the computation of pairwise surface alignments, we can then apply an efficient point matching scheme, which we extended to surface points. Due to the discrete representation of the molecules' shapes and properties, multiple alignments can be computed from pairwise alignments in a straight forward way. One hurdle that needs to be overcome, however, is the large number of surface points that we consider. In this talk, the application of the presented pairwise as well as multiple surface alignment algorithms will be demonstrated on two sets of molecules: a set of eight thermolysin inhibitors, and a set of seven HIV-1 protease inhibitors. Flyer
May 30th, 2007 Systems Biology at FCC -From Theory to Application
  Henning Schmidt, Fraunhofer Chalmers Research Centre
  The Bioinformatics and Systems Biology group at the Fraunhofer Chalmers Research Centre (FCC) provides an integrated approach to the study of biochemical and physiological processes, from the analysis of sequence data to the analysis of dynamic phenomena on a systems level. We develop mathematical methods and tools that aid to delineate and better understand the underlying cause of a disease or phenomenon at both the gene and mechanistic level, i.e., in terms of sequence data, quantitative data and its relation to biochemical reaction or interaction networks. In this talk I will present work that I have been carrying out during the last years at FCC. The goal is to give an overview over past, recent, and planned activities, modeling projects, method and tool development.
May 15th, 2007 Applications of Probability in Genetics, Ecology and Population Genetics
  John Moriarty, UCC
  I will give an overview of the UCC Probability group's work at the interface between probability, statistics and biology. This includes recent past work on circle covering problems from genetics, current investigations in entropy estimation problems in ecology, and planned future work in monte carlo methods in population genetics. Flyer
May 9th, 2007 Differentiation and Integration by cells: The Cellular Calculus
  Phil Hodgkin, The Walter and Eliza Hall Institute of Medical Research, Victoria, Australia
  There are many regulators of lymphocytes that alter the rates of proliferation and affect differentiation, the change of cells from one type to another. In this talk I will explore more closely how differentiation of lymphocytes is regulated by signals added alone and together. Key findings include:
  • Lymphocytes operate as if composed of a series of independent machines governing times to divide, die and differentiate.
  • These machines are 'stochastic' making each cell slightly different.
  • Changes in the likelihood of differentiation are often linked to progressive cell division.
  • Regulatory signals affect the mean and possibly the variance of the probability distributions governing the internal machinery.
  • The extreme heterogeneity in fate of individual cells following stimulation of a population can be described accurately by interleaving independent probability distributions governing times to divide, die as well as the divisions at which differentiation occurs.
  • Conflicting decisions of fate taken at the same time are often resolved with a hierarchy of priority.
It is possible to incorporate these experimental rules into models that provide an accurate, quantitative and internally regulable simulation of lymphocyte growth and regulation. Flyer
Apr. 25th, 2007 Evolutionary Escape on Fitness Landscapes
  Niko Beerenwinkel, Harvard University, Program for Evolutionary Dynamics
  The evolution of HIV within individual patients is associated with disease progression and failure of antiretroviral drug therapy. Using graphical models we describe the development of HIV drug resistance mutations and show how these models improve predictions of the clinical outcome of combination therapy. We present combinatorial algorithms for computing the risk of escape of an evolving population on a given fitness landscape. The method is applied to calculating the likelihood of therapy failure as a function of the viral genotype. Thus, it presents a step towards personalized antiretroviral treatment. Flyer
Mar. 22nd, 2007 Modelling the immune response using probabilistic concepts
  Phil Hodgkin, The Walter and Eliza Hall Institute of Medical Research.
  When lymphocytes, the primary mediators of immunity, are stimulated they proliferate and their rate of growth, survival and differentiation is highly regulated by the receipt of soluble and cell contact mediated signals. This complex system is well suited to experimental dissection, and offers a useful testing ground for developing concepts in systems biology.
A major tool in measuring and analysing the immune response is flow cytometry. Careful quantitative experiments with this method have revealed how cells follow a combination of relatively simple cellular rules operating independently. In this seminar I will discuss how these rules can be used to develop quantitative models of cell growth and the generation of cellular diversity that emerges during the immune response. An important theme of my talk will be that intrinsic stochastic cellular variability, easily dismissed as noise, may have evolved to be an essential feature of immune regulation. Flyer
Mar. 21st, 2007 Analysis of Metabolic Responses
  Fernando Ortega, University of Birmingham.
  Predicting the responses of intact cellular systems to environmental and genetic changes has not been an easy task. Two of the major challenges to understand metabolic responses are the structural complexity of the molecular networks sustaining cellular functioning and the non-linearity inherent in the interaction and kinetic laws involved. In the development of metabolic control analysis (MCA), some strategies have been devised to deal with these difficulties. Regarding network complexity, top-down or modular strategies have been proposed. To deal with non-linearity two assumptions have been made. The first is that metabolic perturbations and responses are small, so that they can be described using a first order infinitesimal treatment. The second assumption is that in vivo enzyme catalysed reaction rates are proportional to the corresponding enzyme concentrations. However, many, if not most, of the responses exhibited by metabolic systems subject to environmental changes or genetic manipulations involve large changes in metabolic variables.To deal with this problem, we proposed an extension of MCA that can be applied to arbitrarily large responses. Control and elasticity coefficients for large changes are defined. These fulfil summation and connectivity theorems, from which expressions for the control coefficients as a function of elasticity coefficients (and the inverse design expressions) are obtained. In addition, the new formalism can be applied in a top-down way to study the control of large metabolic responses in intact cells. This will be exemplified with data reported in the literature. Flyer
Feb. 21st, 2007 Modelling Environmental Fluctuations in Biochemical Systems
  Andrea Rocco, University of Oxford.
  Stochasticity is an essential ingredient of complex behaviours in biological systems. I introduce a theoretical framework to model environmental stochastic fluctuations in metabolic networks. Non-trivial effects are predicted at both the kinetic and systemic levels of description. In particular I propose the concept of control by noise as a way of tuning the systemic behaviour of metabolisms. This rests on a generalisation of standard Metabolic Control Analysis when external fluctuations are considered, which is based upon proper extensions of the Summation Theorems for flux and concentration control coefficients. Finally I will discuss some applications and plans for future research. Flyer
Dec. 6th, 2006 Duplication-Divergence and proteome evolution
  Tim Rutjes
  Current interest in biological interaction networks has focused on applications of graph theoretical tools to real interaction data. One such application concerns the dynamics of proteome evolution. The proteome evolution process is commonly described by a duplication-divergence (DD)-model. I will present and discuss a recent DD-model. In particular, I will discuss the evolution of a large or giant connected component. An interesting observation is that a component can split up during evolution. We investigated this theoretically and numerically. I will also present some variations on the DD-model and outline some recommendations for future research.
Dec. 6th, 2006 Modelling mammalian cell culture proliferation
  Thomas Schröck
  Using experimental data from a joint project between UCD and NUIM, two mathematical models have been created: (1) a simple growth kinetics model that uses a small set of ODEs; and (2) an age distributed cell cycle modelusing PDEs. In this talk, I will review the biological background of cell culture experiments and cell behaviour. Different methods of analysing experiment data will be discussed, some of which have direct applications in biological research. I present the above mentioned models, along with methods to optimise a set of parameters.
Nov. 23rd, 2006 Systems Biology of Sponges: Understanding the evolution of integration in animals - New input from systems biology?
  Michael Nickel, Department of Zoology, Biological Institute, Stuttgart University
June 7th, 2006 Control and system theory for biochemical reaction networks
  Jan H. van Schuppen, CWI, Amsterdam.
  The research is motivated by the aim to understand how a living cell functions. Another motivation, more long term, is to assist the pharmaceutical industry with rational drug design and to assist companies in biotechnology. This program is in the spirit of the systems biology approach and it is executed in cooperations with biologists of the Vrije Universiteit (Hans Westerhoff, Barbara Bakker, Frank Bruggeman, etc.). A biochemical reaction networks will be modelled as a positive control system. Dynamical system properties and system theoretic properties will be described. The problem of rational drug design will be formulated as a control problem and an approach will be discussed. The approach will be illustrated for glycolysis in Trypanosoma brucei. The problem of system reduction is motivated by the very large size of dynamic systems obtained for realistic modeling of biochemical reaction networks in a cell. First results and the approach to the research project for system reduction will be presented including the example of glycolysis in yeast. System identification is another problem of biochemical reaction networks which requires attention and suggestions for an approach will be presented. One aspect is the construction of observers which are used to obtain predictions of the state of a positive system. The research program of the speaker for this area will be summarized and basic problems for positive systems will be mentioned.
March 24th, 2006 New 'Dimensions' in Genome Annotation
  Prof. Bernhard Palsson, UC San Diego
June 17th, 2005 Validation of Biochemical Network Models using Robust Control Theory
  Dr. Declan G. Bates, Control & Instrumentation Group University of Leicester, UK
  Joint Seminar with the Institute of Immunology, NUI Maynooth
May 31st, 2005 An Overview of Computational and Theoretical Immunology
  Prof. Alan S. Perelson, Los Alamos National Laboratory, USA.
  Joint Seminar with the Institute of Immunology, NUI Maynooth
Feb. 23rd, 2005 Some theoretical aspects of cell signaling: receptor-ligand interactions and signal amplification cascades
  Dr. Madalena Chaves, Rutgers University and Sanofi Aventis
Oct. 8th, 2004 Monotone Input-Output Systems: Theory and Its Applications to Molecular Biology
  Prof. David Angeli, Dipartimento di Sistemi e Informatica, Universita degli Studi di Firenze, Italy
Oct. 22nd, 2004 How the brain keeps the eyes still.....and what happens if it fails
  Prof. Richard Abadi, Faculty of Life Sciences, University of Manchester
Sept. 15th & 23rd, 2004 Systems Biology: Introduction to Biology in Neurosciences
  Applied Neurotherapeutics Research Group, University College Dublin and Trinity College
July 21st 2004 Systems Biology: Towards Organizing Principles of Cellular Dynamics
  Prof. Kwang-Hyun Cho, School of Electrical Engineering, University of Ulsan, Korea
July 8th, 2004 Control Engineering in Systems Biology
  Dr. Eric Bullinger, Institute for Systems Theory in Engineering, Univ. of Stuttgart, Germany
March 26th, 2004 Dynamic Modelling of Signal Transduction Pathways "Simulating what cannot be simulated"
  Prof. Olaf Wolkenhauer, Systems Biology and Bioinformatics Group, Institute for Informatics, University of Rostock, Germany
Feb. 20th, 2004 System Dynamics of Epidemics
  Dr. Stephen Duncan, Department of engineering Science, University of Oxford
Feb. 5th, 2004 Concurrent Models of Biochemical Pathways
  Prof. Muffy Calder, Department of Computing Science, University of Glasgow

Past events
Aug 15-18 2010 3rd International Workshop on Systems Biology
  Hamilton Institute
  Link to website
Aug 18-19 2010 1st Symposium on Systems Approaches to Parkinson's Disease
  Hamilton Institute
  Link to website
Aug 17-20, 2008 2nd International Workshop on Systems Biology iwSB
Jul 25th, 2007 E.T.S. Walton Lecture: Divide and conquer: The remarkable story of our immune defense system
  Dr. Phil Hodgkin, Walter and Eliza Hall Inst., Australia
  Fifty years ago Macfarlane Burnet published a two page manuscript that came to be seen as one of the most important scientific papers of the 20th Century. In this paper Burnet outlined the principles for understanding immunity - the remarkable ability of our bodies to detect and eliminate a vast range of potential disease causing organisms. Burnet's idea solved a centuries old problem and precipitated a tremendous burst of experimental investigation into the detailed operation of the immune system that continues to this day and has had a major impact on human health. In this anniversary year of Burnet's landmark paper, I will re-examine the problem of immune specificity and highlight the many medical triumphs that occurred both before and after Burnet’s grand synthesis. In addition I will outline the state of immune knowledge today and look at some of the great challenges facing us if we are to further unlock the power of our immune systems for medical benefit. While the story of immunity illustrates the importance of scientific ideas and empirical discovery there is also a subplot. As a result of Burnet's ideas in the 1950s the small medical research community in Melbourne, where Burnet worked, became an international centre for immunology and established scientific traditions that continue strongly to the present day. Thus, remembering Burnet's paper in its anniversary year serves to illustrate the immense social and economic benefits that flow from supporting creative individuals and how their ideas continue to resonate within, and inspire, a community for many decades.
Jul 17-19, 2006 1st International Workshop on Systems Biology
Sep 1-2, 2005 2nd Workshop on Systems Biology
Jun 14th, 2005 1st Workshop on Systems Biology