Sökning: "False discovery rate"
Visar resultat 1 - 5 av 13 avhandlingar innehållade orden False discovery rate.
1. Statistical analysis of metagenomic data
Sammanfattning : Metagenomics is the study of microbial communities on the genome level by direct sequencing of environmental and clinical samples. Recently developed DNA sequencing technologies have made metagenomics widely applicable and the field is growing rapidly. LÄS MER
2. Extreme Value Analysis of Huge Datasets: Tail Estimation Methods in High-Throughput Screening and Bioinformatics
Sammanfattning : This thesis presents results in Extreme Value Theory with applications to High-Throughput Screening and Bioinformatics. The methods described here, however, are applicable to statistical analysis of huge datasets in general. The main results are covered in four papers. LÄS MER
3. In silico prediction of CIS-regulatory elements
Sammanfattning : As one of the most fundamental processes for all life forms, transcriptional regulation remains an intriguing and challenging subject for biomedical research. Experimental efforts towards understanding the regulation of genes is laborious and expensive, but can be substantially accelerated with the use of computational predictions. LÄS MER
4. Resampling in network modeling of high-dimensional genomic data
Sammanfattning : Network modeling is an effective approach for the interpretation of high-dimensional data sets for which a sparse dependence structure can be assumed. Genomic data is a challenging and important example. In genomics, network modeling aids the discovery of biological mechanistic relationships and therapeutic targets. LÄS MER
5. Selectivity in NMR and LC-MS Metabolomics : The Importance of Sample Preparation and Separation, and how to Measure Selectivity in LC-MS Metabolomics
Sammanfattning : Until now, most metabolomics protocols have been optimized towards high sample throughput and high metabolite coverage, parameters considered to be highly important for identifying influenced biological pathways and to generate as many potential biomarkers as possible. From an analytical point of view this can be troubling, as neither sample throughput nor the number of signals relates to actual quality of the detected signals/metabolites. LÄS MER