Darmstadt, Techn. Universiẗat, Diss., 2002.

Berlin, Humboldt-University, Diss., 2001.

This paper discusses the development of a new information representation system embodied in ontology and the Semantic Web. The new system differs from other representation systems in that it is based on a more sophisticated semantic representation of information, aims to go well beyond the document level, and designed to be understood and processed by machine. A common theme underlying these three features, i.e., turning documents into meaningful interchangeable data, reflects a rising use expectation nurtured by modern technology and, at the same time, presents a unique challenge for its enabling technologies.

Discusses persistent links or PURLs as a tool for linking.

No description available.

No description available.

Introduction The present study evaluated reported methodological characteristics of GWAS, investigating relationships between reported methodological characteristics and outcomes observed. Methods GWAS were identified from NHGRI’s catalogue of GWAS (2005 to 2009). Multivariate meta-regression models (random effects) were produced to identify the impact of reported study characteristics and the strength of relationships between the variables and outcomes. Results The summary odds ratios for replication components of GWAS in cancer was 1.34 (95% CI 1.25, 1.43) and neuropsychiatric disorders was 1.43 (95% CI 1.30, 1.57). Heterogeneity was accounted for by nature of the control group, relationship between case/control groups, whether cases/controls were drawn from the same population, if data was a primary collection or a build on pre-existing data, if quality assurance was reported, and if the study reported power/sample size. Conclusion Evidence supports the existence of variability in reporting, with index components demonstrating less variability than replication components in the GWAS.

Introduction The present study evaluated reported methodological characteristics of GWAS, investigating relationships between reported methodological characteristics and outcomes observed. Methods GWAS were identified from NHGRI’s catalogue of GWAS (2005 to 2009). Multivariate meta-regression models (random effects) were produced to identify the impact of reported study characteristics and the strength of relationships between the variables and outcomes. Results The summary odds ratios for replication components of GWAS in cancer was 1.34 (95% CI 1.25, 1.43) and neuropsychiatric disorders was 1.43 (95% CI 1.30, 1.57). Heterogeneity was accounted for by nature of the control group, relationship between case/control groups, whether cases/controls were drawn from the same population, if data was a primary collection or a build on pre-existing data, if quality assurance was reported, and if the study reported power/sample size. Conclusion Evidence supports the existence of variability in reporting, with index components demonstrating less variability than replication components in the GWAS.

Waves of bovine genomic data have been produced as a result of the bovine genome sequencing projects. In addition to the massive amounts of genomic sequence, significant annotation including single nucleotide polymorphisms, sequence tagged sites and haplotype blocks have been produced by the Bovine HapMap Project. Furthermore, many agriculturally significant traits in cattle such as milk yield and carcass weight are measured on a quantitative scale and have been genetically mapped as quantitative trait loci (QTL). QTL data can be used to generate another form of bovine annotation linking phenotype to genotype. However, it is impossible for humans to be able to analyze genomic scale data without computer based tools. Bioinformatic tools have been shown to greatly increase productivity and improve efficiency when dealing with large data sets. My dissertation presents an integrated, extensible database that houses SNPs, STSs, haplotypes, and QTL. The database is presented to researchers through a restructured, object oriented Bovine QTL Viewer that displays multiple levels of bovine annotation synergistically. Evaluation of use of the viewer was performed using a survey based approach and measured quantitatively. In addition, the QTL data from the database was used to analyze the frequency of gene ontology (GO) annotations within QTL regions. QTL regions were divided into 8 trait based groups. GO terms were counted within each category of QTL and in non- QTL regions of the genome. Top level GO term frequencies were generated from the counts and these frequencies were compared between QTL and non-QTL portions of the genome. Furthermore, specific sets of GO terms believed to be related to QTL categories were also used to determine if QTL regions were enriched for genes annotated with such GO terms. As a result, we determined that gene density varied significantly across QTL regions and that many QTL categories showed GO term frequency differences that could be related to the trait’s biology. Furthermore, our selected GO term sets were shown to be significantly enriched in some QTL categories.

No description available.