Hochschulschrift
Integrierte bioinformatische Methoden zur reproduzierbaren und transparenten Hochdurchsatz-Analyse von Life Science Big Data
Zusammenfassung: High-throughput techniques have lead life sciences into a new era. The genome sequencing of patients is already daily practice in several University hospitals. Furthermore, the systematic in vitro screening of hundreds of thousands of small molecules, has become a standard method for the identification of new drugs in the pharmaceutical industry. The concomitant growth of resulting data and its high complexity, challenges life-science research and brings life-sciences inevitably closer to information technology.The present doctoral thesis deals with the analysis of life science big data with a focus on transparency and reproducibility thereof. Based on a framework for data processing (Galaxy) an analysis platform for the study of genomes and small chemical molecules was developed.For genome analysis, a variety of functions, ranging from functional annotation of prokaryotic and eukaryotic genomes up to the preparation of sequences for their submission into public databases, have been developed. Popular tools such as BLAST were integrated into Galaxy as well as specialized tools, e.g. for the prediction of gene clusters. The flexibility and strength of this analysis platform was demonstrated on six annotated organisms and a number of pharmaceutically relevant Galaxy workflows.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Deutsch
- Notes
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Albert-Ludwigs-Universität Freiburg, Dissertation, 2015
- Classification
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Biowissenschaften, Biologie
- Keyword
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Genanalyse
Bioinformatik
Computational chemistry
Open Source
Open Source
Chemie
SMIL
Biowissenschaften
Bioinformatik
Reproduzierbarkeit
Text Mining
Genomik
Computational chemistry
Freiburg im Breisgau
- Event
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Veröffentlichung
- (where)
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Freiburg
- (who)
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Universität
- (when)
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2015
- Creator
- Contributor
- DOI
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10.6094/UNIFR/11024
- URN
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urn:nbn:de:bsz:25-freidok-110245
- Rights
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:50 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Object type
- Hochschulschrift
Associated
- Grüning, Björn
- Günther, Stefan
- Universität
Time of origin
- 2015