Thesis (Ph.D.) -- University of Texas at Arlington, 2008.

published_or_final_version / abstract / toc / Electrical and Electronic Engineering / Master / Master of Philosophy

Thesis (Ph. D.)--Washington State University, May 2008. / Includes bibliographical references (p. 88-98).

Thesis (Ph. D.)--Duke University, 2008.

Thesis (Ph.D.) - University of Queensland, 2004. / Includes bibliography.

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (p. 257-268).

Being able to predict the sequence-structure relationship in proteins will extend the scope of many bioinformatics tools relying on structure information. Here we use Hidden Markov models (HMM) to recognize and pinpoint the location in target sequences of local structural motifs (local descriptors of protein structure, LDPS) These substructures are composed of three or more segments of amino acid backbone structures that are in proximity with each other in space but not necessarily along the amino acid sequence. We were able to align descriptors to their proper locations in 41.1% of the cases when using models solely built from amino acid information. Using models that also incorporated secondary structure information, we were able to assign 57.8% of the local descriptors to their proper location. Further enhancements in performance was yielded when threading a profile through the Hidden Markov models together with the secondary structure, with this material we were able assign 58,5% of the descriptors to their proper locations. Hidden Markov models were shown to be able to locate LDPS in target sequences, the performance accuracy increases when secondary structure and the profile for the target sequence were used in the models.

Tourette Syndrome (TS) is a neurodevelopmental disorder that starts in childhood. It is marked by multiple motor and vocal tics and a fluctuating course with recurrent time periods of symptom exacerbation followed by symptom remission. TS is considered a disorder of complex etiology that involves the interaction of multiple genetic and environmental factors. Previous studies have implicated regulation of the immune system in TS patients, although this remains a matter of debate. <br>Here we present a genome-wide gene expression study comparing data from TS patients at time points of symptom exacerbation and remission as well as upon symptom onset for newly diagnosed patients, with differentially gene expression analysis, co-expression analysis and pathway analysis. Although the fold change of each regulated gene was very mild, it is the first time that changes in the regulation of the immune system have been implicated at different time points in TS patients.<br><br>

Neurodevelopmental disorders such as autism spectrum disorder (ASD) and psychiatric disorders, for example, schizophrenia (SCZ) represent a large spectrum of disorders that manifest through cognitive and behavioural problems. ASD and SCZ are both highly heritable, and some phenotypic similarities between ASD and SCZ have sparked an interest in understanding their genetic commonalities. The genetics of both disorders exhibit significant heterogeneity. Developments in genomics and systems biology, continually increases people’s understanding of these disorders. Recently, pathogenic genetic variants in the regulatory factor X (RFX) family of transcription factors have been identified in a number of ASD cases. In this thesis, common genetic variants and expression patterns of genes identified to have a conserved promotor X-Box motif region, a binding site of RFX factors, are studied. Significant common variants identified through expression quantitative trait loci (eQTLs) and genome wide association studies (GWAS) are mapped to the regulatory regions of these genes and analysed for putative enrichment. In addition, single-cell RNA sequencing data is utilised to examine enrichment of cell types having high X-Box gene expression in the developing human cortex. Through the study, genes that have eQTLs or SNPs in the genomic regulatory regions of the X-Box genes have been identified. While there were no eQTLs or GWAS SNPs in the X-Box motifs, in the X-Box promoter regions some common variants were found. By hypergeometric distribution testing and the subsequent p-values obtained, all of these distributions are statistically under-enriched. Further, major cell types in the cortical region with increased expression of the X-Box genes and most expressed genes among these enriched cell types have been identified. Among the 11 cell types seven were found to be enriched for X-Box genes and many of the most expressed genes in these cell-types were similar. A further study into the cell types and genes identified, along with additional systems biological data analysis, could reveal a larger list of X-Box genes involved in ASD and SCZ and the specific roles of these genes.

In this study, we have created a simulation model which is concerned about digesting cellulose, as a major component of microalgae in a bioreactor. This model is designed to generate a computational model that simulates the process of granulation in anaerobic sludge and aims to investigate scenarios of possible granular bioaugmentation. Once a mature granule is formed, pro- tein is used as an alternative substrate that will be supplied to a mature granule. Protein, being a main component of cyanobacteria, will promote growth and incorporation of a cell type that can degrade protein (selective pressure). The model developed in a cDynoMiCs simulation environment successfully demonstrated the process of granule formation and bioaugmentation in an Anaerobic granule. Bioaugmentation is a common strategy in the field of wastewater treatment, used to in- troduce a new metabolic capability to either aerobic or anaerobic granules. The end product of our work is a model that can visually demonstrate varying stratifications of different trophic microbial groups that will be of help for the engineers and researchers, who are operating both laboratory and industrial-scale anaerobic digesters and wish to enhance reactor performance. The working model that we have developed has been validated using the existing literature and lab experiments. The model successfully demonstrates granulation in a cellobiose fed system with formation of 0.63 mm mature granule in 59 days with the production of good amount of methane that could be used commercially as a green fuel. This model is extended to perform bioaugmentation by chaining different simulations.