Thesis (M.S.)--Humboldt State University, 2006. / Includes bibliographical references (leaves 19-29). Also available via Humboldt Digital Scholar.

Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (p. 107-114).

Thesis (Ph.D.)--University of Delaware, 2006. / Principal faculty advisor: David A. Hutchins, College of Marine and Earth Studies. Includes bibliographical references.

Thesis (Ph.D.)--University of Nebraska-Lincoln, 2006. / Title from title screen (site viewed May 8, 2007). PDF text: xi, 207 p. : ill. (some col.), maps ; 2.21Mb UMI publication number: AAT 3237058. Includes bibliographical references. Also available in microfilm and microfiche formats.

Thesis (Ph.D.) in Marine Biology--University of Maine, 2008. / Includes vita. Includes bibliographical references (leaves 150-163).

This thesis documents the research that has led to advances in the Artificial Neural Network (ANN) approach to analysing flow cytometric data from phytoplankton cells. The superiority of radial basis function networks (RBF) over multi-layer perception networks (MLP), for data of this nature, has been established, and analysis of 62 marine species of phytoplankton represents an advancement in the number of classes investigated. The complexity and abundance of heterogeneous phytoplankton populations, renders an original multi-class network redundant each time a novel species is encountered. To encompass the additional species, the original multiclass network requires complete retraining, involving long optimisation procedures to be carried out by ANN scientists. An alternative multiple network approach presented (and compared to the multi-class network), allows identification of the expanse of real world data sets and the easy addition of new species. The structure comprises a number of pre-trained single species networks as the front end to a combinatorial decision process for determining species identification. The simplicity of the architecture, and of the subsequent data produced by the technique, allows scientists unfamiliar with ANNs to dynamically alter the species of interest as required, without the need for complete re-training. Kohonens Self Organising Map (SOM), capable of discovering its own classification scheme, indicated areas of discrepancy between flow cytometric signatures of some species and their respective morphological groupings. In an attempt to improve identification to taxonomic group or genus level by supervised networks, class labels more reflective of flow cytometric signatures must be introduced. Methods for boundary recognition and cluster distinction in the output space of the SOM have been investigated, directed towards the possibility of an alternative flow cytometric structuring system. Performance of the alternative multiple network approach was comparable to that of the original multi-class network when identifying data from various environmental and laboratory culturing conditions. Improved generalisation can be achieved through employment of optical characteristics more representative of those found in nature.

No description available.

A rapid increase in the amount of available pathogen genetic data, which is ongoing and likely to continue for the foreseeable future, presents new opportunities and challenges in molecular epidemiology, and in the emerging field of “phylodynamics”, which seeks to unify the study of the evolutionary and epidemiological dynamics of pathogen populations. This thesis explores some of these challenges and opportunities, with a focus on pathogens infecting livestock and poultry. I conducted analyses of sequences from two serotypes of foot-and-mouth-disease virus (FMDV) in order to investigate the global population dynamics of the virus. For serotype SAT 2, the amount of publicly available genomic data is still small enough that all of it could be included in a single analysis. A particular focus was the origins of historical outbreaks occurring in North Africa and the Middle East, outside the endemic area for the serotype. The results suggested sources for these in countries just south of the Sahara, and that the viruses responsible for three outbreaks occurring in 2012 were the result of separate introductions. For serotype O, including every available sequence was not feasible and the data had to be sub-sampled. Little research has been conducted on how to design a sampling strategy for sequence analysis of pathogens, an issue of increasing importance, so a simulation study was conducted to identify one. This suggested that, when reconstructing the temporal and spatial dynamics of a structured population of pathogens or infected individuals, it is preferable to stratify by subpopulation and by time period. The type O analysis itself showed that the south-east Asian topotype moves between countries according to cattle trade networks, but that geographic proximity is also important for strains from southern Asia and the Middle East. With genetic data available at an epidemiological resolution that was previously inconceivable, there are opportunities for new types of inference. For example, if we can acquire a sequence from all or most infected cases in an epidemic, they can inform inference of who infected who, complementing traditional contact-tracing approaches. I introduce a novel phylodynamic method for the simultaneous reconstruction of phylogeny and transmission tree for an epidemic in a situation where every infected host or premises can be identified and a sequence acquired from most of them. The performance of this method was demonstrated using simulated data, and then it was applied to reconstruct both trees from the 2003 H7N7 avian influenza outbreak in the Netherlands.

Magister Scientiae - MSc / Wetlands account for approximately 20% of annual global methane emissions. Many wetlands receive inputs of organic matter, nutrients, metals and various toxic compounds from adjacent agricultural and industrial areas. The present study aimed to investigate the microbial composition of a natural methanogenic consortium. A consortium-based molecular approach to study diversity of methanogenic microbial communities in a natural wetland at the primary inflow was used. Key microorganisms of a nethane producing consortium were identified. Extracted high molecular mss DNA ws analysed by PCR combined with denaturing gradient gel electrophoresis and subsequent sequencing of 16S rDNA. This study was also aimed to identify syntrophic microorganisms in the wetland system. The data obtained suggest a well established syntrophic relationship within the wetland. / South Africa

No description available.