Studies in biological surface science: microfluidics, photopatterning and artificial bilayers

Herein is presented the collective experimental record of research performed in the Laboratory for Biological Surface Science. These investigations are generally classified under the category of bioanalytical surface science and include the following projects. Chapters III and IV describe the creation of a microfluidic device capable of generating fixed arrays of concentration gradients. Experimental results were matched with computational fluid dynamics simulations to predict analyte distributions in these systems. Chapters V and VI demonstrate the discovery and utility of photobleaching fluorophores for micropatterning applications. Bleached fluorophores were found to rapidly attach to electron rich surfaces and this property was used to pattern enzymes inside microfluidic channels in situ. Finally, Chapter VII exhibits a method by which solid supported lipid bilayers can be dried and preserved by specifically bound proteins. The intrinsic property of lateral lipid mobility was maintained during this process and a mechanism by which the protein protects the bilayer was suggested

Technical report of data mining

No abstract availabl

Dynamic Protocol Reverse Engineering a Grammatical Inference Approach

Round trip engineering of software from source code and reverse engineering of software from binary files have both been extensively studied and the state-of-practice have documented tools and techniques. Forward engineering of protocols has also been extensively studied and there are firmly established techniques for generating correct protocols. While observation of protocol behavior for performance testing has been studied and techniques established, reverse engineering of protocol control flow from observations of protocol behavior has not received the same level of attention. State-of-practice in reverse engineering the control flow of computer network protocols is comprised of mostly ad hoc approaches. We examine state-of-practice tools and techniques used in three open source projects: Pidgin, Samba, and rdesktop . We examine techniques proposed by computational learning researchers for grammatical inference. We propose to extend the state-of-art by inferring protocol control flow using grammatical inference inspired techniques to reverse engineer automata representations from captured data flows. We present evidence that grammatical inference is applicable to the problem domain under consideration

Analyzing Granger causality in climate data with time series classification methods

Attribution studies in climate science aim for scientifically ascertaining the influence of climatic variations on natural or anthropogenic factors. Many of those studies adopt the concept of Granger causality to infer statistical cause-effect relationships, while utilizing traditional autoregressive models. In this article, we investigate the potential of state-of-the-art time series classification techniques to enhance causal inference in climate science. We conduct a comparative experimental study of different types of algorithms on a large test suite that comprises a unique collection of datasets from the area of climate-vegetation dynamics. The results indicate that specialized time series classification methods are able to improve existing inference procedures. Substantial differences are observed among the methods that were tested

AVATAR - Machine Learning Pipeline Evaluation Using Surrogate Model

© 2020, The Author(s). The evaluation of machine learning (ML) pipelines is essential during automatic ML pipeline composition and optimisation. The previous methods such as Bayesian-based and genetic-based optimisation, which are implemented in Auto-Weka, Auto-sklearn and TPOT, evaluate pipelines by executing them. Therefore, the pipeline composition and optimisation of these methods requires a tremendous amount of time that prevents them from exploring complex pipelines to find better predictive models. To further explore this research challenge, we have conducted experiments showing that many of the generated pipelines are invalid, and it is unnecessary to execute them to find out whether they are good pipelines. To address this issue, we propose a novel method to evaluate the validity of ML pipelines using a surrogate model (AVATAR). The AVATAR enables to accelerate automatic ML pipeline composition and optimisation by quickly ignoring invalid pipelines. Our experiments show that the AVATAR is more efficient in evaluating complex pipelines in comparison with the traditional evaluation approaches requiring their execution

Leveraging -omics based approaches to explore environments: A look at two domains of life

Rapid advancements in technology have both dramatically lowered the cost of sequencing as well as increased the depth of information gleaned. With such a low barrier of entry, increasing numbers of scientists around the globe are generating unprecedented amounts of data pertaining to the identity and function of the various microbes that impact assorted environments, from within a host to various biomes in nature. Understandably, a pressing challenge in the field centers on how to process and interpret these large quantities of precise information. The leveraging of -omics based techniques used in bioinformatics stands poised to answer this challenge, enabling discoveries that probe not just what a microbe can do, but also perhaps provide a look into their past through an analysis of their genetic potential.For my overall project, I sought to leverage various -omics based approaches to study how various organisms impact and have been impacted by their respective environments. My work has spread from transcriptomics to proteomics and finally metagenomics, from pure cultures to environmental samples, and from fungi to bacteria. At the surface levels, these works provide a form of functional profile of the studied organisms; however, deeper insights into the potential evolutionary history can also be made. For example, the study on the anaerobic gut fungal phylum Neocallimastigomycota (Chapter I) can provide insights into the clade's intertwined history with the development of herbivory, the study on the obligate plant symbiont Rhizophagus irregularis (Chapter II) can provide insight into fungal association with plants, the metagenomic studies of the Binatota (Chapter III) and novel Desulfobacterota classes (Chapter IV) can provide insights into the development and evolution of the Delta Proteobacteria into a diverse clade, and the study of novel Myxococcota classes (Chapter V) can provide clues into the development of predation strategies in bacteria. As a whole, this body of works provides a jumping-off point for future probes into these organisms, as well as potential isolation strategies for the uncultured organisms discussed