Advanced Visual Analytics Approaches for the Integrative Study of Genomic and Transcriptomic Data

DSpace Repository

Show simple item record

dc.contributor.advisor Nieselt, Kay (Apl. Prof.)
dc.contributor.author Jäger, Günter
dc.date.accessioned 2016-06-24T09:07:31Z
dc.date.available 2016-06-24T09:07:31Z
dc.date.issued 2016-06-24
dc.identifier.other 471060526 de_DE
dc.identifier.uri http://hdl.handle.net/10900/70759
dc.identifier.uri http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-707591 de_DE
dc.identifier.uri http://dx.doi.org/10.15496/publikation-12172
dc.description.abstract The advances in next-generation sequencing (NGS) technology enabled rapid and cost-effective whole genome analyses. Nowadays, it is known that individual organisms have unique genome sequences and that differences between these sequences are the reason for genetic diversity. Furthermore, the biomolecular processes of living organisms are steered by genes and the interplay of their products. Perturbations in these systems often lead to disease. Thus, one of the major question in biomedical research is how genetic variations influence gene function, and how these affect underlying biological pathways and gene interaction networks. One of the most common sources of genetic diversity are single nucleotide variations (SNVs). So-called Genome Wide Association Studies (GWAS) as well as expression Quantitative Trait Locus (eQTL) studies intend to associate SNVs with e.g. disease related binary or quantitative traits. However, available methods are usually limited to statistical analyses and previous approaches to improve the interpretation of the respective results are often insufficient. The goal of this dissertation was the development of new visual analytical approaches to assist purely statistical methods in the identification, characterization and interpretation of SNVs. Genomic variations, especially SNVs, also play an important role in the immensely growing field of paleogenetics, where DNA of ancient origin is compared to modern DNA with the intention to gain insights into evolutionary history. In this dissertation, a computational pipeline for comparative NGS analyses of ancient and modern DNA samples has been described. Special attention was given to the read merging step, which is required to cope with the quality limitations inherent to ancient DNA (aDNA), in particular DNA fragmentation and nucleotide misincorporation. In addition, aDNA is usually only retrievable in low amounts and it is often contaminated with DNA of modern microorganisms. To solve this issue, a highly economical microarray-based DNA capturing strategy has been developed for the parallel detection and enrichment of aDNA from up to 100 different human pathogens. en
dc.language.iso en de_DE
dc.publisher Universität Tübingen de_DE
dc.rights ubt-podno de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_ohne_pod.php?la=de de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_ohne_pod.php?la=en en
dc.subject.classification Visual Analytics , Genomik de_DE
dc.subject.ddc 500 de_DE
dc.subject.ddc 570 de_DE
dc.subject.ddc 004 de_DE
dc.title Advanced Visual Analytics Approaches for the Integrative Study of Genomic and Transcriptomic Data en
dc.type Dissertation de_DE
dcterms.dateAccepted 2016-04-20
utue.publikation.fachbereich Informatik de_DE
utue.publikation.fakultaet 7 Mathematisch-Naturwissenschaftliche Fakultät de_DE
utue.publikation.fakultaet 7 Mathematisch-Naturwissenschaftliche Fakultät de_DE

Dateien:

This item appears in the following Collection(s)

Show simple item record