Computational Techniques for Analysis of Genetic Network Dynamics

In this paper we propose modeling and analysis techniques for genetic networks that provide biologists with insight into the dynamics of such systems. Central to our modeling approach is the framework of hybrid systems and our analysis tools are derived from formal analysis of such systems. Given a set of states characterizing a property of biological interest P, we present the Multi-Affine Rectangular Partition (MARP) algorithm for the construction of a set of infeasible states I that will never reach P and the Rapidly Exploring Random Forest of Trees (RRFT) algorithm for the construction of a set of feasible states F that will reach P. These techniques are scalable to high dimensions and can incorporate uncertainty (partial knowledge of kinetic parameters and state uncertainty). We apply these methods to understand the genetic interactions involved in the phenomenon of luminescence production in the marine bacterium V. fischeri

Spatiotemporal localization of proteins in microorganisms via photoactivated localization microscopy

Photoactivated localization microscopy (PALM) is a single molecule fluorescence microscopy technique (SMLM) that relies on the controlled activation and imaging of photo-activatable/convertible fluorescent proteins to determine their position with nanometer scale precision. The analysis of SMLM data is composed of two sequential aspects: the generation of a super-resolution table/image and the subsequent analysis. In recent years, several data analysis packages dedicated to the generation of super-resolved images have been developed. These packages have been extensively characterized and compared in a community-wide effort, therefore allowing researchers to identify optimal solutions for their experiments and providing software developers with a gold standard. On the contrary, the development of data analysis packages dedicated to the study of protein coordinates has been lagging behind, and no comprehensive approach has been developed to date. Here, I present a combination of Fiji and R based scripts for the characterization, filtering and quality assurance of SMLM derived localizations. Furthermore, I demonstrate that specific conventional image analysis techniques can be applied, both quantitatively and qualitatively, to super resolution images. I then apply these analysis tools exemplarily on the characterization of the spatio-temporal localization of a novel DNA repair system in Corynebacterium glutamicum, termed Dip (DNA damage induced protein) C. Finally, I combine the multiple data analysis packages that I developed and/or adapted for the study of specific biological scenarios into a single cohesive pipeline, therefore providing a generalized and comprehensive approach toward the coordinate based analysis of the spatio-temporal localization of proteins in PALM and, in general, in SMLM. Each of the data analysis packages that comprise the pipeline is here presented together with the biological scenario that prompted its development. These include the study of magnetosome formation in Magnetospirillum gryphiswaldense, the study of the chromosome segregation machinery in C. glutamicum and the study of flagellar organization in Trypanosoma brucei.Die photoaktivierte Lokalisationsmikroskopie (PALM) ist eine Einzelmolekül-Fluoreszenzmikroskopie Technik (SMLM), die auf der kontrollierten Aktivierung und Aufnahme von photoaktivierbaren / konvertierbaren fluoreszierenden Proteinen beruht, um ihre Position mit einer Präzision im Nanometerbereich zu bestimmen. Die Analyse von SMLM-Daten besteht aus zwei aufeinander folgenden Aspekten: der Erzeugung einer Tabelle / eines hochauflösenden Bildes und der anschließenden Analyse. In den letzten Jahren wurden mehrere Datenanalysepakete entwickelt, die sich der Berechnung der hochaufgelösten Bilder widmen. Diese Pakete wurden in gemeinschaftsweiten Anstrengungen umfassend charakterisiert und verglichen, sodass Forscher eine optimale Lösung für eigene Experimente wählen können, während Softwareentwicklern einen Goldstandard zur Hand haben. Gegensätzlich wurde jedoch die Entwicklung von Datenanalysepaketen zur spezifischen Untersuchung von Proteinkoordinaten vernachlässigt, so dass in diesem Bereich keine umfassenden Instrumente existieren. In dieser Arbeit präsentiere ich eine Kombination aus Fiji- und R basierten Skripten zur Charakterisierung, Filterung und Qualitätssicherung von SMLM Proteinkoordinaten. Darüber hinaus zeige ich, dass bestimmte konventionelle Bildanalysetechniken sowohl quantitativ als auch qualitativ auf „Superresolution“ Bilder angewandt werden können. Im Folgenden verwende Ich diese Analysewerkzeuge dann beispielhaft zur Charakterisierung der räumlich-zeitlichen Lokalisierung eines neuartigen DNA-Reparatursystems in Corynebacterium glutamicum, welches ich DipC (DNA-Schaden-induziertes Protein) genannt habe. Schließlich kombiniere ich die genannten Datenanalysepakete, die ich für die Untersuchung spezifischer biologischer Szenarien entwickelt und / oder angepasst habe, zu einer einzigen zusammenhängenden Arbeitsroutine. Diese bietet einen allgemeinen und umfassenden Ansatz für die koordinatenbasierte Analyse der räumlich-zeitlichen Lokalisierung von Proteinen aus PALM- und im Allgemeinen aus SMLM-Experimenten. Jedes der Datenanalysepakete, die in beschriebener Routine enthalten sind, wird hier zusammen mit dem biologischen Szenario vorgestellt, das zu ihrer Entwicklung geführt hat. Dazu gehören die Untersuchung der Magnetosomenbildung in Magnetospirillum gryphiswaldense, die Untersuchung der Chromosomensegregationsmaschinerie in C. glutamicum und die Untersuchung der Flagellenorganisation in Trypanosoma brucei

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

Harnessing Knowledge, Innovation and Competence in Engineering of Mission Critical Systems

This book explores the critical role of acquisition, application, enhancement, and management of knowledge and human competence in the context of the largely digital and data/information dominated modern world. Whilst humanity owes much of its achievements to the distinct capability to learn from observation, analyse data, gain insights, and perceive beyond original realities, the systematic treatment of knowledge as a core capability and driver of success has largely remained the forte of pedagogy. In an increasingly intertwined global community faced with existential challenges and risks, the significance of knowledge creation, innovation, and systematic understanding and treatment of human competence is likely to be humanity's greatest weapon against adversity. This book was conceived to inform the decision makers and practitioners about the best practice pertinent to many disciplines and sectors. The chapters fall into three broad categories to guide the readers to gain insight from generic fundamentals to discipline-specific case studies and of the latest practice in knowledge and competence management

Harnessing Knowledge, Innovation and Competence in Engineering of Mission Critical Systems

This book explores the critical role of acquisition, application, enhancement, and management of knowledge and human competence in the context of the largely digital and data/information dominated modern world. Whilst humanity owes much of its achievements to the distinct capability to learn from observation, analyse data, gain insights, and perceive beyond original realities, the systematic treatment of knowledge as a core capability and driver of success has largely remained the forte of pedagogy. In an increasingly intertwined global community faced with existential challenges and risks, the significance of knowledge creation, innovation, and systematic understanding and treatment of human competence is likely to be humanity's greatest weapon against adversity. This book was conceived to inform the decision makers and practitioners about the best practice pertinent to many disciplines and sectors. The chapters fall into three broad categories to guide the readers to gain insight from generic fundamentals to discipline-specific case studies and of the latest practice in knowledge and competence management

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 408)

This bibliography lists 84 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during Dec. 1995. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

Opportunities and challenges for biosensors and nanoscale analytical tools for pandemics: COVID-19

Biosensors and nanoscale analytical tools have shown a huge growth in literature in the past 20 years, with a large number of reports on the topic of ’ultra-sensitive’, ’costeffective’ and ’early-detection’ tools with a potential of ’mass-production’ cited on the web of science. Yet none of these tools are commercially available in the market or practically viable for mass production and use in pandemic diseases such as COVID-19. In this context, we review the technological challenges and opportunities of current bio/chemical sensors and analytical tools by critically analyzing the bottlenecks which have hindered the implementation of advanced sensing technologies in pandemic diseases. We also describe in brief COVID-19 by comparing it with other pandemic strains such as SARS and MERS for the identification of features that enable biosensing. Moreover, we discuss visualization and characterization tools that can potentially be used not only for sensing applications but also assist in speeding up the drug discovery and vaccine development process. Furthermore, we discuss the emerging monitoring mechanism, namely wastewater-based epidemiology, for early warning of the outbreak, focusing on sensors for rapid and on-site analysis of SARS-COV-2 in sewage. To conclude, we provide holistic insights into challenges associated with the quick translation of sensing technologies, policies, ethical issues, technology adoption, and an overall outlook of the role of the sensing technologies in pandemics