Engineering a novel self-powering electrochemical biosensor

This paper records the efforts of a multi-disciplinary team of undergraduate students from Glasgow University to collectively design and carry out a 10 week project in Synthetic Biology as part of the international Genetic Engineered Machine competition (iGEM). The aim of the project was to design and build a self-powering electrochemical biosensor called ‘ElectrEcoBlu’. The novelty of this engineered machine lies in coupling a biosensor with a microbial fuel cell to transduce a pollution input into an easily measurable electrical output signal. The device consists of two components; the sensor element which is modular, allowing for customisation to detect a range of input signals as required, and the universal reporter element which is responsible for generating an electrical signal as an output. The genetic components produce pyocyanin, a competitive electron mediator for microbial fuel cells, thus enabling the generation of an electrical current in the presence of target chemical pollutants. The pollutants tested in our implementation were toluene and salicylate. ElectrEcoBlu is expected to drive forward the development of a new generation of biosensors. Our approach exploited a range of state-of-the-art modelling techniques in a unified framework of qualitative, stochastic and continuous approaches to support the design and guide the construction of this novel biological machine. This work shows that integrating engineering techniques with scientific methodologies can provide new insights into genetic regulation and can be considered as a reference framework for the development of biochemical systems in synthetic biology

Computational Techniques for the Structural and Dynamic Analysis of Biological Networks

The analysis of biological systems involves the study of networks from different omics such as genomics, transcriptomics, metabolomics and proteomics. In general, the computational techniques used in the analysis of biological networks can be divided into those that perform (i) structural analysis, (ii) dynamic analysis of structural prop- erties and (iii) dynamic simulation. Structural analysis is related to the study of the topology or stoichiometry of the biological network such as important nodes of the net- work, network motifs and the analysis of the flux distribution within the network. Dy- namic analysis of structural properties, generally, takes advantage from the availability of interaction and expression datasets in order to analyze the structural properties of a biological network in different conditions or time points. Dynamic simulation is useful to study those changes of the biological system in time that cannot be derived from a structural analysis because it is required to have additional information on the dynamics of the system. This thesis addresses each of these topics proposing three computational techniques useful to study different types of biological networks in which the structural and dynamic analysis is crucial to answer to specific biological questions. In particu- lar, the thesis proposes computational techniques for the analysis of the network motifs of a biological network through the design of heuristics useful to efficiently solve the subgraph isomorphism problem, the construction of a new analysis workflow able to integrate interaction and expression datasets to extract information about the chromo- somal connectivity of miRNA-mRNA interaction networks and, finally, the design of a methodology that applies techniques coming from the Electronic Design Automation (EDA) field that allows the dynamic simulation of biochemical interaction networks and the parameter estimation

Algorithms for Modular Self-reconfigurable Robots: Decision Making, Planning, and Learning

Modular self-reconfigurable robots (MSRs) are composed of multiple robotic modules which can change their connections with each other to take different shapes, commonly known as configurations. Forming different configurations helps the MSR to accomplish different types of tasks in different environments. In this dissertation, we study three different problems in MSRs: partitioning of modules, configuration formation planning and locomotion learning, and we propose algorithmic solutions to solve these problems. Partitioning of modules is a decision-making problem for MSRs where each module decides which partition or team of modules it should be in. To find the best set of partitions is a NP-complete problem. We propose game theory based both centralized and distributed solutions to solve this problem. Once the modules know which set of modules they should team-up with, they self-aggregate to form a specific shaped configuration, known as the configuration formation planning problem. Modules can be either singletons or connected in smaller configurations from which they need to form the target configuration. The configuration formation problem is difficult as multiple modules may select the same location in the target configuration to move to which might result in occlusion and consequently failure of the configuration formation process. On the other hand, if the modules are already in connected configurations in the beginning, then it would be beneficial to preserve those initial configurations for placing them into the target configuration as disconnections and re-connections are costly operations. We propose solutions based on an auction-like algorithm and (sub) graph-isomorphism technique to solve the configuration formation problem. Once the configuration is built, the MSR needs to move towards its goal location as a whole configuration for completing its task. If the configuration’s shape and size is not known a priori, then planning its locomotion is a difficult task as it needs to learn the locomotion pattern in dynamic time – the problem is known as adaptive locomotion learning. We have proposed reinforcement learning based fault-tolerant solutions for locomotion learning by MSRs

Tales of Research Misconduct: A Lacanian Diagnostics of Integrity Challenges in Science Novels

research integrity; scientific misconduct; science novels; Lacanian psychoanalysis; continental philosophy; falsification; plagiarism; ethic

Modelling bacterial regulatory networks with Petri nets

To exploit the vast data obtained from high throughput molecular biology, a variety of modelling and analysis techniques must be fully utilised. In this thesis, Petri nets are investigated within the context of computational systems biology, with the specific focus of facilitating the creation and analysis of models of biological pathways. The analysis of qualitative models of genetic networks using safe Petri net techniques was investigated with particular reference to model checking. To exploit existing model repositories a mapping was presented for the automatic translation of models encoded in the Systems Biology Markup Language (SBML) into the Petri Net framework. The mapping is demonstrated via the conversion and invariant analysis of two published models of the glycolysis pathway. Dynamic stochastic simulations of biological systems suffer from two problems: computational cost; and lack of kinetic parameters. A new stochastic Petri net simulation tool, NASTY was developed which addresses the prohibitive real-time computational costs of simulations by using distributed job scheduling. In order to manage and maximise the usefulness of simulation results a new data standard, TSML was presented. The computational power of NASTY provided the basis for the development of a genetic algorithm for the automatic parameterisation of stochastic models. This parameter estimation technique was evaluated on a published model of the general stress response of E. coli. An attempt to enhance the parameter estimation process using sensitivity analysis was then investigated. To explore the scope and limits of applying the Petri net techniques presented, a realistic case study investigated how the Pho and aB regulons interact to mitigate phosphate stress in Bacillus subtilis. This study made use of a combination of qualitative and quantitative Petri net techniques and was able to confirm an existing experimental hypothesis.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Modelling bacterial regulatory networks with Petri nets

To exploit the vast data obtained from high throughput molecular biology, a variety of modelling and analysis techniques must be fully utilised. In this thesis, Petri nets are investigated within the context of computational systems biology, with the specific focus of facilitating the creation and analysis of models of biological pathways. The analysis of qualitative models of genetic networks using safe Petri net techniques was investigated with particular reference to model checking. To exploit existing model repositories a mapping was presented for the automatic translation of models encoded in the Systems Biology Markup Language (SBML) into the Petri Net framework. The mapping is demonstrated via the conversion and invariant analysis of two published models of the glycolysis pathway. Dynamic stochastic simulations of biological systems suffer from two problems: computational cost; and lack of kinetic parameters. A new stochastic Petri net simulation tool, NASTY was developed which addresses the prohibitive real-time computational costs of simulations by using distributed job scheduling. In order to manage and maximise the usefulness of simulation results a new data standard, TSML was presented. The computational power of NASTY provided the basis for the development of a genetic algorithm for the automatic parameterisation of stochastic models. This parameter estimation technique was evaluated on a published model of the general stress response of E. coli. An attempt to enhance the parameter estimation process using sensitivity analysis was then investigated. To explore the scope and limits of applying the Petri net techniques presented, a realistic case study investigated how the Pho and aB regulons interact to mitigate phosphate stress in Bacillus subtilis. This study made use of a combination of qualitative and quantitative Petri net techniques and was able to confirm an existing experimental hypothesis.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Landscapes of the invisible: sounds, cosmologies and poetics of space

In this PhD by Publication I revisit and contextualize art works and essays I have collaboratively created under the name Flow Motion between 2004-13, in order to generate new insights on the contributions they have made to diverse and emerging fields of contemporary arts practice/research, including digital, virtual, sonic and interdisciplinary art. The works discussed comprise the digital multimedia installation and sound art performance Astro Black Morphologies/Astro Dub Morphologies (2004-5), the sound installation and performance Invisible (2006-7), the web art archive and performance presentation project promised lands (2008-10), and two related texts, Astro Black Morphologies: Music and Science Lovers (2004) and Music and Migration (2013). I show how these works map new thematic constellations around questions of space and diaspora, music and cosmology, invisibility and spectrality, the body and perception. I also show how the works generate new connections between and across contemporary avant-garde, experimental and popular music, and visual art and cinema traditions. I describe the methodological design, approaches and processes through which the works were produced, with an emphasis on transversality, deconstruction and contemporary black music forms as key tools in my collaborative artistic and textual practice. I discuss how, through the development of methods of data translation and transformation, and distinctive visual approaches for the re-elaboration of archival material, the works produced multiple readings of scientific narratives, digital X-ray data derived from astronomical research on black holes and dark energy, and musical, photographic and textual material related to historical and contemporary accounts of migration. I also elaborate on the relation between difference and repetition, the concepts of multiplicity and translation, and the processes of collective creation which characterize my/Flow Motion’s work. The art works and essays I engage with in this commentary produce an idea of contemporary art as the result of a fluid, open and mutating assemblage of diverse and hybrid methods and mediums, and as an embodiment of a cross-cultural, transversal and transdisciplinary knowledge shaped by research, process, creative dialogues, collaborative practice and collective signature

Continental Philosophy of Technoscience

The key objective of this volume is to allow philosophy students and early-stage researchers to become practicing philosophers in technoscientific settings. Zwart focuses on the methodological issue of how to practice continental philosophy of technoscience today. This text draws upon continental authors such as Hegel, Engels, Heidegger, Bachelard and Lacan (and their fields of dialectics, phenomenology and psychoanalysis) in developing a coherent message around the technicity of science or rather, “technoscience”. Within technoscience, the focus will be on recent developments in life sciences research, such as genomics, post-genomics, synthetic biology and global ecology. This book uniquely presents continental perspectives that tend to be underrepresented in mainstream philosophy of science, yet entail crucial insights for coming to terms with technoscience as it is evolving on a global scale today. This is an open access book