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1 Online-Ressource (PDF-Datei: 227 Seiten, 23893 Kilobyte)
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Illustrationen (teilweise farbig), Diagramme (teilweise farbig)
Content:
Alzheimerkrankheit, SNP, Genomik, Proteomanalyse, Metabolomik, Maschinelles Lernen, miRNS, Herzinfarkt, Nichtalkoholische Fettleberhepatitis
Content:
Humanity is plagued by many diseases. Beside environmental influences, many --- if not all --- diseases are also subject to genetic predisposition and then display molecular alterations such as proteomic or metabolic aberrations. The elucidation of the molecular principles underlying human diseases is one of the prime goals of biomedical research. To this end, there has been an advent of large-scale omics profiling studies. While the field of molecular biology has experienced tremendous development, data analysis remains a bottleneck. In the context of this thesis, we developed a number of analysis strategies for different types of omics data resulting from different experimental settings. These include approaches for associations studies for plasma miRNAs and time-resolved plasma omics data. Furthermore, we devised analyses of different RNA-Seq transcriptome profiling studies coping with problems such as lack of replicates or multifactorial experimental design. We also designed machine learning frameworks for the identification of discriminatory biomolecular signatures analysing case-control or time-to-event data. All of the strategies mentioned above were developed and applied in the contexts of multi-disciplinary endeavours. They aided in the identification of plasma miRNAs associated with age, sex, and BMI as well as plasma miRNAs bearing potential as diagnostic biomarkers for non-alcoholic fatty liver disease (NAFLD). This thesis significantly contributed to a study ...
Note:
Literaturverzeichnis: Seite 91-110
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Dissertation Mathematisch-Naturwissenschaftliche Fakultät der Ernst-Moritz-Arndt-Universität Greifswald 2017
Additional Edition:
Erscheint auch als Druck-Ausgabe Kacprowski, Tim Omics profiling and biomarker mining for common diseases Greifswald, 2017
Language:
English
Subjects:
Biology
Keywords:
Alzheimerkrankheit
;
SNP
;
Genomik
;
Proteomanalyse
;
Metabolomik
;
Maschinelles Lernen
;
miRNS
;
Herzinfarkt
;
Nichtalkoholische Fettleberhepatitis
;
Biomarker
;
Hochschulschrift
URN:
urn:nbn:de:gbv:9-002974-0
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