Computing has evolved from isolated machines, providing calculative support of applications, toward communication networks that provide functional support to groups of people and embedded systems. Perhaps, one of the most compelling feature and benefit of computers is their overwhelming computing efficiency. Today, we conceive distributed computational systems of an ever-increasing sophistication, which we then apply in various settings – critical support functions of our society just to name one important application area. The spread and impact of computing, in terms of so-called information society technologies, has obviously gained a very high momentum over the years and today it delivers a technology that our societies have come to depend on. To this end, concerns related to our acceptance of qualities of computing, e.g., dependability, are increasingly emphasized by users as well as vendors. An indication of this increased focus on dependability is found in contemporary efforts of mitigating the effects from systemic failures in critical infrastructures, e.g., energy distribution, resource logistics, and financial transactions. As such, the dependable function of these infrastructures is governed by means of more or less autonomic computing systems that interact with cognitive human agents. However, due to intricate system dependencies as well as being situated in our physical environment, even the slightest – unanticipated – perturbation in one of these embedded systems can result in degradations or catastrophic failures of our society. We argue that this contemporary problem of computing mainly is due to our own difficulties in modeling and engineering the involved system complexities in an understandable manner. Consequently, we have to provide support for dependable computing systems by means of new methodologies of systems engineering. From a historical perspective, computing has evolved, from being supportive of quite well defined and understood tasks of algorithmic computations, into a disruptive technology that enables and forces change upon organizations as well as our society at large. In effect, a major challenge of contemporary computing is to understand, predict, and harness the involved systems’ increasing complexity in terms of constituents, dependencies, and interactions – turning them into dependable systems. In this thesis, we therefore introduce a model of open computational systems, as the means to convey these systems’ factual behavior in realistic situations, but also in order to facilitate our own understanding of how to monitor and control their complex interdependencies. Moreover, since the critical variables that govern these complex systems’ qualitative behavior can be of a very elusive nature, we also introduce a method of online engineering, whereby cognitive agents – human and software – can instrument these open computational systems according to their own subjective and temporal understanding of some complex situation at hand.

This chapter presents the Infobiotics Workbench (IBW), an integrated software suite developed for computational systems biology. The tool is built upon stochastic P systems, a probabilistic extension of P systems, as modelling framework. The platform utilises computer-aided modelling and analysis of biological systems through simulation, verification and optimisation. IBW allows modelling and analysing not only cell level behaviour, but also multi-compartmental population dynamics. This enables comparing be tween macroscopic and mesoscopic interpretations of molecular interaction networks and investigating temporo-spatial phenomena in multicellular systems. These capabilities make IBW a useful, coherent and comprehensive in silico tool for systems biology research.

Thesis (MSc)--Stellenbosch University, 2011. / ENGLISH ABSTRACT: Progress in computational systems biology depends crucially on the availability of generic rate equations that accurately describe the behaviour and regulation of catalysed processes over a wide range of conditions. Such equations for ordinary enzyme-catalysed reactions have been developed in our group and have proved extremely useful in modelling metabolic networks. However, these networks link to growth and reproduction processes through template-directed synthesis of macromolecules such as polynucleotides and polypeptides. Lack of an equation that captures such a relationship led us to derive a generic rate equation that describes catalysed, template-directed polymerisation reactions with varying monomer stoichiometry and varying chain length. A model describing the mechanism of a generic template-directed polymerisation process in terms of elementary reactions with mass action kinetics was developed. Maxima, a computational algebraic solver, was used to determine analytical expressions for the steady-state concentrations of the species in the equation system from which a steady-state rate equation could be derived. Using PySCeS, a numerical simulation platform developed in our group, we calculated the time-dependent evolution and the steadystates of the species in the catalytic mechanisms used in the derivation of the rate equations. The rate equation was robust in terms of being accurately derived, and in comparison with the rates determined with PySCeS. Addition of more elongation steps to the mechanism allowed the generalisation of the rate equation to an arbitrary number of elongations steps and an arbitrary number of monomer types. To test the regulatory design of the system we incorporated the generic rate equation in a computational model describing a metabolic system consisting of multiple monomer supplies linked by a template-directed demand reaction. Rate characteristics were chosen to demonstrate the utility of the simplified generic rate equation. The rate characteristics provided a visual representation of the control and regulation profile of the system and showed how this profile changes under varying conditions. / AFRIKAANSE OPSOMMING: Die beskikbaarheid van generiese snelheidsvergelykings wat die gedrag en regulering van gekataliseerde prosesse akkuraat oor ’n wye reeks omstandighede beskryf is van kardinale belang vir vooruitgang in rekenaarmatige sisteembiologie. Sulke vergelykings is in ons groep ontwikkel vir gewone ensiem-gekataliseerde reaksies en blyk uiters nuttig te wees vir die modellering van metaboliese netwerke. Hierdie netwerke skakel egter deur templaat-gerigte sintese van makromolekule soos polinukleotiede en polipeptiede aan groei- en voorplantingsprosesse. Die gebrek aan vergelykings wat sulke verwantskappe beskryf het ons genoop om ’n generiese snelheidsvergelyking af te lei wat gekataliseerde, templaatgerigte polimerisasie-reaksies met wisselende monomeerstoigiometrie en kettinglengte beskryf. ’n Model wat die meganisme van ’n generiese templaat-gerigte polimerisasie-proses in terme van elementêre reaksies met massa-aksiekinetika beskryf is ontwikkel. Maxima, ’n rekenaarmatige algebraïese oplosser, is gebruik om analitiese uitdrukkings vir die bestendige- toestand konsentrasies van die spesies in die vergelyking-stelsel te vind. Hierdie uitdrukkings is gebruik om ’n bestendige-toestand snelheidsvergelyking af te lei. Ons het die tyd-afhanklike progressie en die bestendige toestande bereken van die spesies in die katalitiese meganismes wat gebruik is in die afleiding van die snelheidsvergelykings. Die rekenaarprogram PySCeS is ’n numeriese simulasieplatform wat in ons groep ontwikkel is. Die snelheidsvergelyking blyk akkuraat afgelei te wees en is in ooreenstemming met snelhede deur PySCeS bereken. Die toevoeging van verdere verlengingstappe tot die meganisme het dit moontlik gemaak om die snelheidsvergelyking te veralgemeen tot ’n arbitrêre hoeveelheid verlengingstappe en monomeertipes. Om die regulatoriese ontwerp van die sisteem te toets het ons die generiese snelheidsvergelyking in ’n rekenaarmatige model geïnkorporeer wat ’n metaboliese sisteem bestaande uit verskeie monomeer-aanbodblokke en ’n templaatgerigte aanvraagblok beskryf. Snelheidskenmerkanalise is gekies om die nut van die vereenvoudigde generiese snelheidsvergelyking te demonstreer. Met hierdie snelheidskenmerke kon ons die kontrole- en reguleringsprofiel van die stelsel visualiseer en wys hoe hierdie profiel verander onder wisselende omstandighede.

Computational systems biology is an emerging area of research that focuses on understanding the holistic view of complex biological systems with the help of statistical, mathematical and computational techniques. The regulation of gene expression in gene regulatory network is a fundamental task performed by all known forms of life. In this subsystem, modelling the behaviour of the components and their interactions can provide useful biological insights. Statistical approaches for understanding biological phenomena such as gene regulation are proving to be useful for understanding the biological processes that are otherwise not comprehensible due to multitude of information and experimental difficulties. A combination of both the experimental and computational biology can potentially lead to system level understanding of biological systems. This thesis focuses on the problem of inferring the dynamics of gene regulation from the observed output of gene expression. Understanding of the dynamics of regulatory proteins in regulating the gene expression is a fundamental task in elucidating the hidden regulatory mechanisms. For this task, an initial fixed structure of the network is obtained using experimental biology techniques. Given this network structure, the proposed inference algorithms make use of the expression data to predict the latent dynamics of transcription factor proteins. The thesis starts with an introductory chapter that familiarises the reader with the physical entities in biological systems; then we present the basic framework for inference in transcriptional regulation and highlight the main features of our approach. Then we introduce the methods and techniques that we use for inference in biological networks in chapter 2; it sets the foundation for the remaining chapters of the thesis. Chapter 3 describes four well-known methods for inference in transcriptional regulation with pros and cons of each method. Main contributions of the thesis are presented in the following three chapters. Chapter 4 describes a model for inference in transcriptional regulation using state space models. We extend this method to cope with the expression data obtained from multiple independent experiments where time dynamics are not present. We believe that the time has arrived to package methods like these into customised software packages tailored for biologists for analysing the expression data. So, we developed an open-sources, platform independent implementation of this method (TFInfer) that can process expression measurements with biological replicates to predict the activities of proteins and their influence on gene expression in gene regulatory network. The proteins in the regulatory network are known to interact with one another in regulating the expression of their downstream target genes. To take this into account, we propose a novel method to infer combinatorial effect of the proteins on gene expression using a variant of factorial hidden Markov model. We describe the inference mechanism in combinatorial factorial hidden model (cFHMM) using an efficient variational Bayesian expectation maximisation algorithm. We study the performance of the proposed model using simulated data analysis and identify its limitation in different noise conditions; then we use three real expression datasets to find the extent of combinatorial transcriptional regulation present in these datasets. This constitutes chapter 5 of the thesis. In chapter 6, we focus on problem of inferring the groups of proteins that are under the influence of same external signals and thus have similar effects on their downstream targets. Main objectives for this work are two fold: firstly, identifying the clusters of proteins with similar dynamics indicate their role is specific biological mechanisms and therefore potentially useful for novel biological insights; secondly, clustering naturally leads to better estimation of the transition rates of activity profiles of the regulatory proteins. The method we propose uses Dirichlet process mixtures to cluster the latent activity profiles of regulatory proteins that are modelled as latent Markov chain of a factorial hidden Markov model; we refer to this method as DPM-FHMM. We extensively test our methods using simulated and real datasets and show that our model shows better results for inference in transcriptional regulation compared to a standard factorial hidden Markov model. In the last chapter, we present conclusions about the work presented in this thesis and propose future directions for extending this work.

Esta pesquisa apresenta uma contribuição para a avaliação do problema de previsão de posição futura de aeronaves dentro da aviação brasileira. O uso dessas previsões é muito importante para os sistemas de vigilância do espaço aéreo, sobretudo para a detecção de conflitos entre aeronaves. O problema é estudado para vôos em rota, considerando previsões de posição para instantes de 1 a 20 minutos. Primeiramente, o problema é apresentado, de forma que fique claro o contexto de sua aplicação dentro dos sistemas automatizados para a gestão do tráfego aéreo. Em seguida, são mostrados os métodos matemáticos necessários para o estudo da previsão de posição futura de aeronaves em rota. O modelo proposto para se realizar a previsão utiliza a regressão linear das posições conhecidas da aeronave, extrapolando suas possíveis posições futuras. As condições de um vôo em rota permitem a utilização deste método. Os resultados obtidos são comparados com as informações de posições reais das aeronaves, permitindo avaliar a qualidade das posições estimadas. Por fim, são apresentadas formas de se aplicar o modelo proposto dentro de sistemas computacionais utilizados para a previsão de posição futura de aeronaves, permitindo que os sistemas de vigilância do espaço aéreo façam uso das previsões. / This research presents a contribution to the evaluation of the predicting aircraft future positions problem considering the Brazilian airspace. These predictions are very important for airspace surveillance systems, mainly to the detection of conflict among aircraft. The problem is studied for en route flights, considering position predictions from 1 to 20 minutes. Firstly, the problem is proposed, so that its application context to air traffic management automation can be clear. Then, the necessary mathematical methods used to study en route aircraft future position prediction are shown. The proposed model employed to find the predictions makes use of linear regression of known aircraft positions, extrapolating its future positions. En route flight conditions permit this approach. Prediction results are then compared with real aircraft positions, so that position estimates quality can be evaluated. Finally, ways of practical application of the proposed model inside computational systems used for aircraft future position prediction are presented. This allows surveillance airspace systems to make use of the predictions.

Esta pesquisa apresenta uma contribuição para a avaliação do problema de previsão de posição futura de aeronaves dentro da aviação brasileira. O uso dessas previsões é muito importante para os sistemas de vigilância do espaço aéreo, sobretudo para a detecção de conflitos entre aeronaves. O problema é estudado para vôos em rota, considerando previsões de posição para instantes de 1 a 20 minutos. Primeiramente, o problema é apresentado, de forma que fique claro o contexto de sua aplicação dentro dos sistemas automatizados para a gestão do tráfego aéreo. Em seguida, são mostrados os métodos matemáticos necessários para o estudo da previsão de posição futura de aeronaves em rota. O modelo proposto para se realizar a previsão utiliza a regressão linear das posições conhecidas da aeronave, extrapolando suas possíveis posições futuras. As condições de um vôo em rota permitem a utilização deste método. Os resultados obtidos são comparados com as informações de posições reais das aeronaves, permitindo avaliar a qualidade das posições estimadas. Por fim, são apresentadas formas de se aplicar o modelo proposto dentro de sistemas computacionais utilizados para a previsão de posição futura de aeronaves, permitindo que os sistemas de vigilância do espaço aéreo façam uso das previsões. / This research presents a contribution to the evaluation of the predicting aircraft future positions problem considering the Brazilian airspace. These predictions are very important for airspace surveillance systems, mainly to the detection of conflict among aircraft. The problem is studied for en route flights, considering position predictions from 1 to 20 minutes. Firstly, the problem is proposed, so that its application context to air traffic management automation can be clear. Then, the necessary mathematical methods used to study en route aircraft future position prediction are shown. The proposed model employed to find the predictions makes use of linear regression of known aircraft positions, extrapolating its future positions. En route flight conditions permit this approach. Prediction results are then compared with real aircraft positions, so that position estimates quality can be evaluated. Finally, ways of practical application of the proposed model inside computational systems used for aircraft future position prediction are presented. This allows surveillance airspace systems to make use of the predictions.

Technological advances in the recent decades have enabled cancer researchers to probe the disease at multiple resolutions. This wealth of experimental data combined with computational systems biology methods is now leading to predictive models of cancer progression and response to therapy. We begin by presenting our research group’s multis-cale in silico framework for modeling cancer, whose core is a tissue-scale computational model capable of tracking the progression of tumors from a diffusion-limited avascular phase through angiogenesis, and into invasive lesions with realistic, complex morphologies. We adapt this core model to consider the delivery of systemically-administered anticancer agents and their effect on lesions once they reach their intended nuclear target. We calibrate the model parameters using in vitro data from the literature, and demonstrate through simulation that transport limitations affecting drug and oxygen distributions play a significant role in hampering the efficacy of chemotherapy; a result that has since been validated by in vitro experimentation. While this study demonstrates the capability of our adapted core model to predict distributions (e.g., cell density, pressure, oxygen, nutrient, drug) within lesions and consequent tumor morphology, nevertheless, the underlying factors driving tumor-scale behavior occur at finer scales. What is needed in our multi-scale approach is to parallel reality, where molecular signaling models predict cellular behavior, and ultimately drive what is seen at the tumor level. Models of signaling pathways linked to cell models are already beginning to surface in the literature. We next transition our research to the molecular level, where we employ data mining and bioinformatics methods to infer signaling relationships underlying a subset of breast cancer that might benefit from targeted therapy of Androgen Receptor and associated pathways. Defining the architecture of signaling pathways is a critical first step towards development of pathways models underlying tumor models, while also providing valuable insight for drug discovery. Finally, we develop an agent-based, cell-scale model focused on predicting motility in response to chemical signals in the microenvironment, generally accepted to be a necessary feature of cancer invasion and metastasis. This research demonstrates the use of signaling models to predict emergent cell behavior, such as motility. The research studies presented in this dissertation are critical steps towards developing a predictive, in silico computational model for cancer progression and response to therapy. Our Laboratory for Computational & Predictive Oncology, in collaboration with research groups throughout in the United States and Europe are following a computational systems biology paradigm where model development is fueled by biological knowledge, and model predictions are refining experimental focus. The ultimate objective is a virtual cancer simulator capable of accurately simulating cancer progression and response to therapy on a patient-specific basis. / text

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No. of bitstreams: 1 oliveirajunior_ajo_me_bot.pdf: 5639185 bytes, checksum: 41dab40b84e40ca63b845dee1590104f (MD5) Previous issue date: 2016-07-27 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Nos países de clima tropical, como o Brasil, um dos maiores desafios para produção animal e trabalho humano são os fatores ambientais, como altas temperaturas e umidades dentro de ambientes, assim como as tipologias das instalações, muitas vezes limitantes para o desempenho produtivo. O conforto térmico e a ambiência são áreas de estudo que tem por objetivo conceder o bem-estar para indivíduos, sejam eles animais ou seres humanos. Nos dias atuais grande parte das análises de conforto térmico no meio agrícola, ressaltando às em ambientes de produção animal, utilizam índices que possibilitam a avaliação do nível de estresse térmico de um determinado local por meio de variáveis climatológicas, como o Índice de Temperatura e Umidade – ITU, Índice de Temperatura de Globo Negro e Umidade – ITGU e Índice de Temperatura Equivalente – ITEq. Semelhantemente, em locais de trabalho humano há um limite de tolerância para exposição ao calor que deve ser monitorado mediante o chamado Índice de Bulbo Úmido Termômetro de Globo – IBUTG. Para a resolução desses índices, não há atualmente um sistema computacional específico, de hardware e software, que forneça, em tempo real, a condição térmica de um ambiente. Deste modo, o presente trabalho teve por objetivo desenvolver um sistema computacional capaz de avaliar, em tempo real, o conforto térmico de instalações de produção animal e de ambientes de trabalho humano. O sistema foi desenvolvido baseado na criação de um dispositivo portátil para coleta e transmissão das variáveis climatológicas de temperatura do ar, temperatura de globo negro e umidade relativa do ar, e do desenvolvimento de um aplicativo para smartphones e tablets Android. O dispositivo portátil foi desenvolvido utilizando um microcontrolador padrão Arduino, juntamente com sensores de temperatura e umidade relativa do ar. Para o desenvolvimento do aplicativo para dispositivos móveis, foi utilizado a linguagem de programação orientada a objetos Java no ambiente de desenvolvimento integrado Android Studio. O aplicativo para dispositivos móveis e o dispositivo portátil foram aplicados em diferentes ambientes e apresentaram correta medição de variáveis climatológicas e cálculo dos índices de conforto térmico. O dispositivo portátil demonstrou ser um produto funcional na transmissão de dados para dispositivos móveis. / In tropical weather countries, such as Brazil, one of the greatest challenges for animal production and human work environments are environmental factors, among them high temperature and humidity inside of the environments, as well as the type of facilities which are limiting for productive performance. The thermal comfort and the ambience are study areas that aims the well-being of individuals, whether they are animals or humans. It is possible to define thermal comfort as the pleasant thermal sensation of the body, in which are not necessary physiological efforts to keep the body in thermal balance. Nowadays, several analysis of thermal comfort in the agriculture environment, mainly at environments of animal production, apply indexes to make it possible the evaluation of thermal stress level of a specific place through the climatological variables, for instance, the Temperature and Humidity Index – THI, Black Globe-Humidity Index – BGHI and Heat Load Index – HLI. In the same way, at places of human work, there is a tolerance limit for heat exposition that should be monitored by the known Wet-bulb Globe Temperature Index – WBGT index. Currently, for resolution of these indexes, there is not a specific computational system (hardware and software) that provides the thermal comfort of an environment in real time. Therefore, the present work aimed to develop a computational system with features to evaluate in real time the thermal comfort of facilities of animal production and human work. The system was developed based on the creation of a mobile device to collect and transmit weather variables from the air temperature, black globe temperature and relative air humidity, and also the development of an app for smartphones and tablets. The mobile device was developed using the Arduino microcontroller, along with sensors of air temperature and relative humidity. For the development of the app it was used the Java oriented object program language, with the Android integrated development environment. The app for mobile devices and the portable device were applied in different environments and both presented a correctly measurement of climatological variables and the calculating of thermal comfort indexes. The portable device proved to be a functional product in data transmission for mobile devices.

There is an emerging field in the design and development of complex systems, where systems are built upon components which in themselves are large scale systems – system of systems. Among other things, the system of systems viewpoint emphasises on open complex systems. In this thesis, the model of open computational systems is used to convey the constituents, dependencies, and interactions of such complex distributed systems. These open complex systems are exposed to critical events, occurring in the systems execution environment. Moreover, these events may have negative effects on the system at hand, resulting in system behaviour diverging from intended. Also, to take all possible affecting events in consideration when designing the system is impossible. By being able to instrument the system at hand in real time, i.e. online, one may be able to compensate the effects caused by critical events. However, to enable online instrumentation, one needs a supporting methodology which handles issues of an online nature and supporting technologies. In this thesis, this support is enabled by the methodology of online engineering and the technology of visualization. Furthermore, these instrumentations can be performed by cognitive agents – both human and software – which may explore and refine a specific system in conformance with their own, or cooperative, agendas and qualitative goals. To be able to perform the instrumentation, the cognitive agents need to be able to observe the phenomenon at hand to gain situation awareness, which in itself lies as a foundation for the decision process, carried out during the instrumentation phase. With this in mind, one quickly realizes the importance of enabling observation of open computational systems for both human and software cognitive agents. If human cognitive agents are involved in applying the methodology; the requirements on how the system is represented for the observing human agent – how the system is visualized – grows even more important. In this thesis, we emphasise visualization technology as a supporting technology for human cognitive agents in their observation process. By providing human cognitive agents with visualization technology, we may enhance the result of their observation process and thereby also increase the possibility to reach their qualitative goals. Hence, visualization of open computational systems affects a human cognitive agent’s situation awareness, which in itself lies as the foundation for the decision making process on instrumentation of the specific system at hand in conformance with the agent’s qualitative goals. This thesis will present an evaluation of a supporting tool for visualization of systemic qualities in open computational systems. Such tool must supply functions which convey the set of requirements put forward by the selected model, method, and technology. Moreover, the evaluation will be accompanied by appropriate recommendations for improvement of such a tool.

By increasing the level of abstraction in the representation of regulatory network models, we can hope to allow modelers to create models that are beyond the threshold of what can currently be expressed reliably. As hundreds of reactions are difficult to understand, maintain, and extend, thousands of reactions become next to impossible without any automation or aid. Using the multistate-species concept we can reduce the number of reactions needed to represent certain systems and thus, lessen the cognitive load on modelers. A multistate species is an entity with a defined range for state variables, which refers to a group of different forms for a specific species. A multistate reaction involves one or more multistate species and compactly represents a group of similar single reactions. In this work, we have extended JCMB (the JigCell Model Builder) to comply with multistate species and reactions modeling and presented a proposal for enhancing SBML (the Systems Biology Markup Language) standards to support multistate models. / Master of Science