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Deep Groundwater Metagenomics : Computational Analysis of Microbial Communities and Metabolic Pathways

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dc.date.accessioned 2016-01-25T13:38:50Z und
dc.date.accessioned 2017-10-24T12:24:08Z
dc.date.available 2016-01-25T13:38:50Z und
dc.date.available 2017-10-24T12:24:08Z
dc.date.issued 2016-01-25T13:38:50Z
dc.identifier.uri http://radr.hulib.helsinki.fi/handle/10138.1/5256 und
dc.identifier.uri http://hdl.handle.net/10138.1/5256
dc.title Deep Groundwater Metagenomics : Computational Analysis of Microbial Communities and Metabolic Pathways en
ethesis.discipline Computer science en
ethesis.discipline Tietojenkäsittelytiede fi
ethesis.discipline Datavetenskap sv
ethesis.discipline.URI http://data.hulib.helsinki.fi/id/1dcabbeb-f422-4eec-aaff-bb11d7501348
ethesis.department.URI http://data.hulib.helsinki.fi/id/225405e8-3362-4197-a7fd-6e7b79e52d14
ethesis.department Institutionen för datavetenskap sv
ethesis.department Department of Computer Science en
ethesis.department Tietojenkäsittelytieteen laitos fi
ethesis.faculty Matematisk-naturvetenskapliga fakulteten sv
ethesis.faculty Matemaattis-luonnontieteellinen tiedekunta fi
ethesis.faculty Faculty of Science en
ethesis.faculty.URI http://data.hulib.helsinki.fi/id/8d59209f-6614-4edd-9744-1ebdaf1d13ca
ethesis.university.URI http://data.hulib.helsinki.fi/id/50ae46d8-7ba9-4821-877c-c994c78b0d97
ethesis.university Helsingfors universitet sv
ethesis.university University of Helsinki en
ethesis.university Helsingin yliopisto fi
dct.creator Althermeler, Nicole
dct.issued 2016
dct.language.ISO639-2 eng
dct.abstract Metagenomics promises to shed light on the functioning of microbial communities and their surrounding ecosystem. In metagenomic studies the genomic sequences of a collection of microorganisms are directly extracted from a specific environment. Up to 99% of microbes cannot be cultivated in the lab; thus, traditional analysis techniques have very limited applicability in this challenging setting. By directly extracting the sequences from the environment, metagenomic studies circumvents this dilemma. Thus, metagenomics has become a powerful tool in the analysis of the diversity and metabolic capability of environmental microbes. However, metagenomic studies have challenges of their own. In this thesis we investigate several aspects of metagenomic data set analysis, focusing on means of (1) verifying adequacy of taxonomic unit and enzyme representation and annotation in the sample, (2) highlighting similarities between samples by principal component analysis, (3) visualizing metabolic pathways with manually drawn metabolic maps from the Kyoto Encyclopedia of Genes and Genomes, and (4) estimating taxonomic distributions of pathways with a novel strategy. A case study of deep bedrock groundwater metagenomic samples will illustrate these methods. Water samples from boreholes, up to 2500 meter deep, of two different sites of Finland display the applicability and limitations of aforementioned methods. In addition publicly available metagenomic and genomic samples serve as baseline references. Our analysis resulted in a taxonomic and metabolic characterization of the samples. We were able to adequately retrieve and annotate the metabolic content based on the deep bedrock samples. The visualization provided a tool for further investigation. The microbial community distribution could be characterized on higher levels of abstraction. Previously suspected similarities to fungi or archaea were not verified. First promising results were observed with the novel strategy in estimating taxonomic distributions of pathways. Further results can be found at: http://www.cs.helsinki.fi/group/urenzyme/deepfun/ en
dct.language en
ethesis.language.URI http://data.hulib.helsinki.fi/id/languages/eng
ethesis.language English en
ethesis.language englanti fi
ethesis.language engelska sv
ethesis.thesistype pro gradu-avhandlingar sv
ethesis.thesistype pro gradu -tutkielmat fi
ethesis.thesistype master's thesis en
ethesis.thesistype.URI http://data.hulib.helsinki.fi/id/thesistypes/mastersthesis
dct.identifier.urn URN:NBN:fi-fe2017112251161
dc.type.dcmitype Text

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