Theses and Dissertations from UMD

Permanent URI for this communityhttp://hdl.handle.net/1903/2

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM

More information is available at Theses and Dissertations at University of Maryland Libraries.

Browse

Filters

2004 - 200912010 - 20151

Settings

Subject: search.filters.subject.functional genomics

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Epiviz: Integrative Visual Analysis Software for Genomics
    (2015) Chelaru, Florin; Corrada Bravo, Hector; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Computational and visual data analysis for genomics has traditionally involved a combination of tools and resources, of which the most ubiquitous consist of genome browsers, focused mainly on integrative visualization of large numbers of big datasets, and computational environments, focused on data modeling of a small number of moderately sized datasets. Workflows that involve the integration and exploration of multiple heterogeneous data sources, small and large, public and user specific have been poorly addressed by these tools. Commonly, the data visualized in these tools is the output of analyses performed in powerful computing environments like R/Bioconductor or Python. Two essential aspects of data analysis are usually treated as distinct, in spite of being part of the same exploratory process: algorithmic analysis and interactive visualization. In current technologies these are not integrated within one tool, but rather, one precedes the other. Recent technological advances in web-based data visualization have made it possible for interactive visualization tools to tightly integrate with powerful algorithmic tools, without being restricted to one such tool in particular. We introduce Epiviz (http://epiviz.cbcb.umd.edu), an integrative visualization tool that bridges the gap between the two types of tools, simplifying genomic data analysis workflows. Epiviz is the first genomics interactive visualization tool to provide tight-knit integration with computational and statistical modeling and data analysis. We discuss three ways in which Epiviz advances the field of genomic data analysis: 1) it brings code to interactive visualizations at various different levels; 2) takes the first steps in the direction of collaborative data analysis by incorporating user plugins from source control providers, as well as by allowing analysis states to be shared among the scientific community; 3) combines established analysis features that have never before been available simultaneously in a visualization tool for genomics. Epiviz can be used in multiple branches of genomics data analysis for various types of datasets, of which we detail two: functional genomics data, aligned to a continuous coordinate such as the genome, and metagenomics, organized according to volatile hierarchical coordinate spaces. We also present security implications of the current design, performance benchmarks, a series of limitations and future research steps.
  • Thumbnail Image
    Item
    TIME SERIES TRANSCRIPTIONAL PROFILING ANALYSIS OF THE Arabidopsis thaliana USING FULL GENOME DNA MICROARRAY AND METABOLIC INFORMATION
    (2004-08-26) Dutta, Bhaskar; Klapa, Maria I; Quackenbush, John; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    With the advent of the DNA microarray technology, it became possible to study the expression of entire cellular genomes. Tanscriptional profiling alone can not provide a comprehensive picture of the cellular physiological state and it should be complemented by other cellular fingerprints. Transcriptional profiling combined with metabolic information of a systematically perturbed system can unravel the relationship between gene and metabolic regulation. In this context the transcriptional response of Arabidopsis thaliana liquid cultures (grown for 12 days under light and 23 sup oC) to 1-day treatment with 1% CO sub 2 was measured by full genome cDNA microarrays. The Time series gene expression profiles were analyzed in the context of the known Arabidopsis thaliana physiology using multivariate statistics. Data analysis revealed an increase in the rate of CO sub 2 fixation, biomass production and cell wall growth. The breadth of the information obtained from a single experiment validated the significance of the high throughput transcriptional profiling.