At present, compared to our scientific knowledge of how natural biosystems function, we have practically no knowledge of how to engineer biosystems, i.e., how to design, build, repair, maintain, operate, and modify them in a rational and knowledgeable manner. Thus, the EcoCyborg research project was established with the basic intent of making a contribution to the science and engineering of biosystems. / This thesis covers three important arms of study within the overall framework of the EcoCyborg project. The first area is the development and implementation of a workbench for simulation based on composite models. The workbench was designed to accommodate easy integration, synchronization and communication of a number of independent modules. It was developed for use under OS/2 Warp, an operating system that supports multi-process simulation. The functionality of the workbench was tested with a composite model of an EcoCyborg. This composite model contained submodels of an ecosystem, two control systems, and several forcing functions. / The second area is the development and implementation of control systems for biosystems. The control system was intended to guide an ecosystem so that its behavior would best achieve the goals of the controllers which, in this case, were related to the populations of the ecosystem's species. The major part of the work on the control systems was focused on the Pavlovian controller. It mainly covered the investigation of the possibilities to develop and to implement a physiological-level Pavlovian controller. The thesis also presents results from a preliminary investigation on the design and implementation of a cognitive controller. From this, a relatively simple cognitive controller was developed to complement the action of the Pavlovian controller. / The third area is the experimental use of the workbench, and of the Pavlovian and cognitive controllers. For this, ecosystems having various constitutions and their forcing functions were modeled and used in the simulation. Pavlovian controllers with on-off, proportional and proportional plus integral mechanisms were used to control the populations. The cognitive controller was used to maintain minimum population of the various species in the ecosystem. / In general, the workbench that was developed was found suitable to accommodate the simulation of an EcoCyborg composite model. The tools that ware developed for constructing and implementing the Pavlovian controller were tested and found practical and effective for use in constructing Pavlovian controllers of various configurations. The results of the work on the cognitive controller provided useful information for its further development.

Doctorat en Sciences / info:eu-repo/semantics/nonPublished

No description available.

Thesis (MSc (Biochemistry))--University of Stellenbosch, 2009. / A Python package called PySUNDIALS has been developed which provides an interface to the suite of nonlinear di erential/algebraic equation solvers (SUNDIALS) using ctypes as a foreign function interface (FFI). SUNDIALS is a C implementation of a set of modern algorithms for integrating and solving various forms of the initial value problem (IVP). Additionally, arbitrary root nding capabilities, time dependent sensitivity analysis, and the solution of di erential and algebraic systems are available in the various modules provided by SUNDIALS. A signi cant focus of the project was to ensure the python package conforms to Python language standards and syntactic expectations. Multiple examples of the SUNDIALS modules (CVODE, CVODES, IDA and KINSOL) are presented comparing PySUNDIALS to C SUNDIALS (for veri cation of correctness), and comparing PySUNDIALS to various other comparable software packages. The examples presented also provide benchmark comparisons for speed, and code length. Speci c uses of the features of the SUNDIALS package are illustrated, including the modelling of discontinuous events using root nding, time dependent sensitivity analysis of oscillatory systems, and the modelling of equilibrium blocks using a complete set of implicit di erential and algebraic equations. PySUNDIALS is available as open source software for download. It is being integrated into the systems biology software PySCeS as an optional solver set, on an ongoing basis. A brief discussion of potential methods of optimization and the continuation of the project to wrap the parallel processing modules of SUNDIALS is presented.

Thesis (PhD)--Stellenbosch University, 2005. / ENGLISH ABSTRACT: Since their inception, biology and biochemistry have been spectacularly successful in characterising the living cell and its components. As the volume of information about cellular components continues to increase, we need to ask how we should use this information to understand the functioning of the living cell? Computational systems biology uses an integrative approach that combines theoretical exploration, computer modelling and experimental research to answer this question. Central to this approach is the development of computational models, new modelling strategies and computational tools. Against this background, this study aims to: (i) develop a new modelling package: PySCeS, (ii) use PySCeS to study discontinuous behaviour in a metabolic pathway in a way that was very difficult, if not impossible, with existing software, (iii) develop an interactive, web-based repository (JWS Online) of cellular system models. Three principles that, in our opinion, should form the basis of any new modelling software were laid down: accessibility (there should be as few barriers as possible to PySCeS use and distribution), flexibility (pySCeS should be extendable by the user, not only the developers) and usability (PySCeS should provide the tools we needed for our research). After evaluating various alternatives we decided to base PySCeS on the freely available programming language, Python, which, in combination with the large collection of science and engineering algorithms in the SciPy libraries, would give us a powerful modern, interactive development environment. / AFRIKAANSE OPSOMMING: Sedert hul totstandkoming was biologie en, meer spesifiek, biochemie uiters suksesvol in die karakterisering van die lewende sel se komponente. Steeds groei die hoeveelheid informasie oor die molekulêre bestanddele van die sel daagliks; ons moet onself dus afvra hoe ons hierdie informasie kan integreer tot 'n verstaanbare beskrywing van die lewende sel se werking. Om dié vraag te beantwoord gebruik rekenaarmatige sisteembiologie 'n geïntegreerde benadering wat teorie, rekenaarmatige modellering en eksperimenteeIe navorsing kombineer. Sentraal tot die benadering is die ontwikkeling van nuwe modelle, strategieë vir modellering, en sagteware. Teen hierdie agtergrond is die hoofdoelstelling van hierdie projek: (i) die ontwikkeling van 'n nuwe modelleringspakket, PySCeS (ii) die benutting van PySCeS om diskontinue gedrag in n metaboliese sisteem te bestudeer (iets wat met die huidiglik beskikbare sagteware redelik moeilik is), (en iii) die ontwikkeling vann interaktiewe, internet-gebaseerde databasis van sellulêre sisteem modelle, JWS Online. Ons is van mening dat nuwe sagteware op drie belangrike beginsels gebaseer behoort te wees: toeganklikheid (die sagteware moet maklik bekombaar en bruikbaar wees), buigsaamheid (die gebruiker moet self PySCeS kan verander en ontwikkel) en bruikbaarheid (al die funksionalitiet wat ons vir ons navorsing nodig moet in PySCeS ingebou wees). Ons het verskeie opsies oorweeg en besluit om die vrylik verkrygbare programmeringstaal, Python, in samehang die groot kolleksie wetenskaplike algoritmes, SciPy, te gebruik. Hierdie kombinasie verskaf n kragtige, interaktiewe ontwikkelings- en gebruikersomgewing. PySCeS is ontwikkel om onder beide die Windows en Linux bedryfstelsels te werk en, meer spesifiek, om gebruik te maak van 'n 'command line interface'. Dit beteken dat PySCeS op enige interaktiewe rekenaar-terminaal Python ondersteun sal werk. Hierdie eienskap maak ook moontlik die gebruik van PySCeS as 'n modelleringskomponent in 'n groter sagteware pakket onder enige bedryfstelsel wat Python ondersteun. PySCeS is op 'n modulere ontwerp gebaseer, wat dit moontlik vir die eindgebruiker maak om die sagteware se bronkode verder te ontwikkel. As 'n toepassing is PySCeS gebruik om die oorsaak van histeretiese gedrag van 'n lineêre, eindproduk-geïnhibeerde metaboliese pad te ondersoek. Ons het hierdie interessante gedrag in 'n vorige studie ontdek, maar kon nie, met die sagteware wat op daardie tydstip tot ons beskikking was, hierdie studie voortsit nie. Met PySCeS se ingeboude vermoë om parameter kontinuering te doen, kon ons die oorsake van hierdie diskontinuë gedrag volledig karakteriseer. Verder het ons 'n nuwe metode ontwikkel om hierdie gedrag te visualiseer as 'n interaksie tussen die volledige sisteem se subkomponente. Tydens PySCeS se ontwikkeling het ons opgemerk dat dit baie moeilik was om metaboliese modelle wat in die literature gepubliseer is te herbou en te bestudeer. Hierdie situasie is grotendeels die gevolg van die feit dat nêrens 'n sentrale databasis vir metaboliese modelle bestaan nie (soos dit wel bestaan vir genomiese data of proteïen strukture). Die JWS Online databasis is spesifiek ontwikkel om hierdie leemte te vul. JWS Online maak dit vir die gebruiker moontlik om, via die internet en sonder die installasie van enige gespesialiseerde modellerings sagteware, gepubliseerde modelle te bestudeer en ook af te laai vir gebruik met ander modelleringspakkette soos bv. PySCeS. JWS Online het alreeds 'n onmisbare hulpbron vir sisteembiologiese navorsing en onderwys geword.

In this thesis, I have studied CMOS dendrites, implemented them on a reconfigurable analog platform and modeled them using MATLAB Simulink. The dendrite model was further used to build a computational model. I implemented a Hidden Markov Model (HMM) classifier to build a simple YES/NO wordspotter. I also discussed the inter-relation between neural systems, CMOS transistors and HMM networks. The physical principles behind the operation of silicon devices and biological structures are similar. Hence silicon devices can be used to emulate biological structures like dendrites. Dendrites are a branched, conductive medium which connect a neurons synapses to its soma. Dendrites were previously believed to be like wires in neural networks. However, recent research suggests that they have computational power. We can emulate dendrites using transistors in the Field Programmable Analog Array (FPAA). Our lab has built the Reconfigurable Analog Signal Processor (RASP) family of FPAAs which was used for the experiments. I analytically compared the mathematical model of dendrites to our model in silicon. The mathematical model based on the device physics of the silicon devices was then used to simulate dendrites in Simulink. An automated tool, sim2spice was then used to convert the Simulink model into a SPICE netlist, such that it can be implemented on a FPAA. This is an easier tool to use for DSP and Neuromorphic engineers who's primary areas of expertise isn't circuit design.