Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.

Semantic Support for Computational Land-Use Modelling

Postprint

Dynamic load balancing of distributed memory parallel computational mechanics using unstructured meshes for multi-physical modelling

As the complexity of parallel applications increase, the performance limitations resulting from computational load imbalance become dominant. Mapping the problem space to the processors in a parallel machine in a manner that balances the workload of each processors will typically reduce the run-time. In many cases the computation time required for a given calculation cannot be predetermined even at run-time and so static partition of the problem returns poor performance. For problems in which the computational load across the discretisation is dynamic and inhomogeneous, for example multi-physics problems involving fluid and solid mechanics with phase changes, the workload for a static subdomain will change over the course of a computation and cannot be estimated beforehand. For such applications the mapping of loads to process is required to change dynamically, at run-time in order to maintain reasonable efficiency. The issue of dynamic load balancing are examined in the context of PHYSICA, a three dimensional unstructured mesh multi-physics continuum mechanics computational modelling code.

Analysis and modelling of chemical looping combustion process with and without oxygen uncoupling

Effective control and limiting of carbon dioxide (CO₂) emissions in energy production are major challenges of science today. Current research activities include the development of new low-cost carbon capture technologies, and among the proposed concepts, chemical combustion (CLC) and chemical looping with oxygen uncoupling (CLOU) have attracted significant attention allowing intrinsic separation of pure CO₂ from a hydrocarbon fuel combustion process with a comparatively small energy penalty. Both CLC and CLOU utilize the well-established fluidized bed technology, but several technical challenges need to be overcome in order to commercialize the processes. Therefore, development of proper modelling and simulation tools is essential for the design, optimization, and scale-up of chemical looping-based combustion systems. The main objective of this work was to analyze the technological feasibility of CLC and CLOU processes at different scales using a computational modelling approach. A onedimensional fluidized bed model frame was constructed and applied for simulations of CLC and CLOU systems consisting of interconnected fluidized bed reactors. The model is based on the conservation of mass and energy, and semi-empirical correlations are used to describe the hydrodynamics, chemical reactions, and transfer of heat in the reactors. Another objective was to evaluate the viability of chemical looping-based energy production, and a flow sheet model representing a CLC-integrated steam power plant was developed. The 1D model frame was succesfully validated based on the operation of a 150 kWth laboratory-sized CLC unit fed by methane. By following certain scale-up criteria, a conceptual design for a CLC reactor system at a pre-commercial scale of 100 MWth was created, after which the validated model was used to predict the performance of the system. As a result, further understanding of the parameters affecting the operation of a large-scale CLC process was acquired, which will be useful for the practical design work in the future. The integration of the reactor system and steam turbine cycle for power production was studied resulting in a suggested plant layout including a CLC boiler system, a simple heat recovery setup, and an integrated steam cycle with a three pressure level steam turbine. Possible operational regions of a CLOU reactor system fed by bituminous coal were determined via mass, energy, and exergy balance analysis. Finally, the 1D fluidized bed model was modified suitable for CLOU, and the performance of a hypothetical 500 MWth CLOU fuel reactor was evaluated by extensive case simulations.

Primary sex determination of placental mammals: a modelling study uncovers dynamical developmental constraints in the formation of Sertoli and granulosa cells

Primary sex determination in placental mammals is a very well studied developmental process. Here, we aim to investigate the currently established scenario and to assess its adequacy to fully recover the observed phenotypes, in the wild type and perturbed situations. Computational modelling allows clarifying network dynamics, elucidating crucial temporal constrains as well as interplay between core regulatory modules.

Numerical modelling of radiating superorbital flows

Experimental aerodynamic studies of the flows around new aerocapture spacecraft configurations are presently being done in the superorbital expansion tubes at The University of Queensland. Short duration flows at speeds of 10--13 km/s are produced in the expansion tube facility and are then applied to the model spacecraft. Although high-temperature effects, such as molecular dissociation, have long been a part of the computational modelling of the expansion tube flows for speeds below 10 km/s, radiation may now be a significant mechanism of energy transfer within the shock layer on the model. This paper will study the coupling of radiation energy transport for an optically thin gas to the flow dynamics in order to obtain accurate predictions of thermal loads on the spacecraft. The results show that the effect of radiation on the flowfields of subscale models for expansion tube experiments can be assessed by measurements of total heat transfer and radiative heat transfer.

Computational modeling of optical trapping of vaterite microspheres

The ability to grow microscopic spherical birefringent crystals of vaterite, a calcium carbonate mineral, has allowed the development of an optical microrheometer based on optical tweezers. However, since these crystals are birefringent, and worse, are expected to have non-uniform birefringence, computational modeling of the microrheometer is a highly challenging task. Modeling the microrheometer - and optical tweezers in general - typically requires large numbers of repeated calculations for the same trapped particle. This places strong demands on the efficiency of computational methods used. While our usual method of choice for computational modelling of optical tweezers - the T-matrix method - meets this requirement of efficiency, it is restricted to homogeneous isotropic particles. General methods that can model complex structures such as the vaterite particles, such as finite-difference time-domain (FDTD) or finite-difference frequency-domain (FDFD) methods, are inefficient. Therefore, we have developed a hybrid FDFD/T-matrix method that combines the generality of volume-discretisation methods such as FDFD with the efficiency of the T-matrix method. We have used this hybrid method to calculate optical forces and torques on model vaterite spheres in optical traps. We present and compare the results of computational modelling and experimental measurements.

The role of material characterisation in the crush modelling of thermoplastic composite structures

The predictive capability of high fidelity finite element modelling, to accurately capture damage and crush behaviour of composite structures, relies on the acquisition of accurate material properties, some of which have necessitated the development of novel approaches. This paper details the measurement of interlaminar and intralaminar fracture toughness, the non-linear shear behaviour of carbon fibre (AS4)/thermoplastic Polyetherketoneketone (PEKK) composite laminates and the utilisation of these properties for the accurate computational modelling of crush. Double-cantilever-beam (DCB), four-point end-notched flexure (4ENF) and Mixed-mode bending (MMB) test configurations were used to determine the initiation and propagation fracture toughness in mode I, mode II and mixed-mode loading, respectively. Compact Tension (CT) and Compact Compression (CC) test samples were employed to determine the intralaminar longitudinal tensile and compressive fracture toughness. V-notched rail shear tests were used to measure the highly non-linear shear behaviour, associated with thermoplastic composites, and fracture toughness. Corresponding numerical models of these tests were developed for verification and yielded good correlation with the experimental response. This also confirmed the accuracy of the measured values which were then employed as input material parameters for modelling the crush behaviour of a corrugated test specimen.

Modelling and Mining To Manage

In this talk, I will describe various computational modelling and data mining solutions that form the basis of how the office of Deputy Head of Department (Resources) works to serve you. These include lessons I learn about, and from, optimisation issues in resource allocation, uncertainty analysis on league tables, modelling the process of winning external grants, and lessons we learn from student satisfaction surveys, some of which I have attempted to inject into our planning processes.

Multi-physics modelling - A vital component of virtual manufacturing

One of the core tasks of the virtual-manufacturing environment is to characterise the transformation of the state of material during each of the unit processes. This transformation in shape, material properties, etc. can only be reliably achieved through the use of models in a simulation context. Unfortunately, many manufacturing processes involve the material being treated in both the liquid and solid state, the trans-formation of which may be achieved by heat transfer and/or electro-magnetic fields. The computational modelling of such processes, involving the interactions amongst various interacting phenomena, is a consider-able challenge. However, it must be addressed effectively if Virtual Manufacturing Environments are to become a reality! This contribution focuses upon one attempt to develop such a multi-physics computational toolkit. The approach uses a single discretisation procedure and provides for direct interaction amongst the component phenomena. The need to exploit parallel high performance hardware is addressed so that simulation elapsed times can be brought within the realms of practicality. Examples of Multiphysics modelling in relation to shape casting, and solder joint formation reinforce the motivation for this work.

Orchestration of multiscale model for computational oncology

Cancer is a challenging disease that involves multiple types of biological interactions in different time and space scales. Often computational modelling has been facing problems that, in the current technology level, is impracticable to represent in a single space-time continuum. To handle this sort of problems, complex orchestrations of multiscale models is frequently done. PRIMAGE is a large EU project that aims to support personalized childhood cancer diagnosis and prognosis. The goal is to do so predicting the growth of the solid tumour using multiscale in-silico technologies. The project proposes an open cloud-based platform to support decision making in the clinical management of paediatric cancers. The orchestration of predictive models is in general complex and would require a software framework that support and facilitate such task. The present work, proposes the development of an updated framework, referred herein as the VPH-HFv3, as a part of the PRIMAGE project. This framework, a complete re-writing with respect to the previous versions, aims to orchestrate several models, which are in concurrent development, using an architecture as simple as possible, easy to maintain and with high reusability. This sort of problem generally requires unfeasible execution times. To overcome this problem was developed a strategy of particularisation, which maps the upper-scale model results into a smaller number and homogenisation which does the inverse way and analysed the accuracy of this approach.

Interplay Between Cell Growth And Cell Cycle In Plants.

The growth of organs and whole plants depends on both cell growth and cell-cycle progression, but the interaction between both processes is poorly understood. In plants, the balance between growth and cell-cycle progression requires coordinated regulation of four different processes: macromolecular synthesis (cytoplasmic growth), turgor-driven cell-wall extension, mitotic cycle, and endocycle. Potential feedbacks between these processes include a cell-size checkpoint operating before DNA synthesis and a link between DNA contents and maximum cell size. In addition, key intercellular signals and growth regulatory genes appear to target at the same time cell-cycle and cell-growth functions. For example, auxin, gibberellin, and brassinosteroid all have parallel links to cell-cycle progression (through S-phase Cyclin D-CDK and the anaphase-promoting complex) and cell-wall functions (through cell-wall extensibility or microtubule dynamics). Another intercellular signal mediated by microtubule dynamics is the mechanical stress caused by growth of interconnected cells. Superimposed on developmental controls, sugar signalling through the TOR pathway has recently emerged as a central control point linking cytoplasmic growth, cell-cycle and cell-wall functions. Recent progress in quantitative imaging and computational modelling will facilitate analysis of the multiple interconnections between plant cell growth and cell cycle and ultimately will be required for the predictive manipulation of plant growth.

Multiobjective design of viscoelastic laminated composite sandwich panels

The optimal design of laminated sandwich panels with viscoelastic core is addressed in this paper, with the objective of simultaneously minimizing weight and material cost and maximizing modal damping. The design variables are the number of layers in the laminated sandwich panel, the layer constituent materials and orientation angles and the viscoelastic layer thickness. The problem is solved using the Direct MultiSearch (DMS) solver for multiobjective optimization problems which does not use any derivatives of the objective functions. A finite element model for sandwich plates with transversely compressible viscoelastic core and anisotropic laminated face layers is used. Trade-off Pareto optimal fronts are obtained and the results are analyzed and discussed.

Systems biology approaches for the design of novel Saccharomyces cerevisiae winemaking strains for enhanced flavour compounds synthesis

Tese de Doutoramento em Biologia Ambiental e Molecular

Quantitative refinement of reaction-based biomodels

In the field of molecular biology, scientists adopted for decades a reductionist perspective in their inquiries, being predominantly concerned with the intricate mechanistic details of subcellular regulatory systems. However, integrative thinking was still applied at a smaller scale in molecular biology to understand the underlying processes of cellular behaviour for at least half a century. It was not until the genomic revolution at the end of the previous century that we required model building to account for systemic properties of cellular activity. Our system-level understanding of cellular function is to this day hindered by drastic limitations in our capability of predicting cellular behaviour to reflect system dynamics and system structures. To this end, systems biology aims for a system-level understanding of functional intraand inter-cellular activity. Modern biology brings about a high volume of data, whose comprehension we cannot even aim for in the absence of computational support. Computational modelling, hence, bridges modern biology to computer science, enabling a number of assets, which prove to be invaluable in the analysis of complex biological systems, such as: a rigorous characterization of the system structure, simulation techniques, perturbations analysis, etc. Computational biomodels augmented in size considerably in the past years, major contributions being made towards the simulation and analysis of large-scale models, starting with signalling pathways and culminating with whole-cell models, tissue-level models, organ models and full-scale patient models. The simulation and analysis of models of such complexity very often requires, in fact, the integration of various sub-models, entwined at different levels of resolution and whose organization spans over several levels of hierarchy. This thesis revolves around the concept of quantitative model refinement in relation to the process of model building in computational systems biology. The thesis proposes a sound computational framework for the stepwise augmentation of a biomodel. One starts with an abstract, high-level representation of a biological phenomenon, which is materialised into an initial model that is validated against a set of existing data. Consequently, the model is refined to include more details regarding its species and/or reactions. The framework is employed in the development of two models, one for the heat shock response in eukaryotes and the second for the ErbB signalling pathway. The thesis spans over several formalisms used in computational systems biology, inherently quantitative: reaction-network models, rule-based models and Petri net models, as well as a recent formalism intrinsically qualitative: reaction systems. The choice of modelling formalism is, however, determined by the nature of the question the modeler aims to answer. Quantitative model refinement turns out to be not only essential in the model development cycle, but also beneficial for the compilation of large-scale models, whose development requires the integration of several sub-models across various levels of resolution and underlying formal representations.