Sökning: "gene abundance data"
Visar resultat 1 - 5 av 59 avhandlingar innehållade orden gene abundance data.
1. Statistical modelling and analyses of DNA sequence data with applications to metagenomics
Sammanfattning : Microorganisms are organised in complex communities and are ubiquitous in all ecosystems, including natural environments and inside the human gut. Metagenomics, which is the direct sequencing of DNA from a sample, enables studying the collective genomes of the organisms that are there present. LÄS MER
2. 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
3. Modeling of bacterial DNA patterns important in horizontal gene transfer using stochastic grammars
Sammanfattning : DNA contains genes which carry the blueprints for all processes necessary to maintain life. In addition to genes, DNA also contains a wide range of functional patterns, which governs many of these processes. These functional patterns have typically a high variability, both within and between species, which makes them hard to detect. LÄS MER
4. Omics Data Analysis of Complex Diseases and Traits
Sammanfattning : Following the advent of the high-throughput techniques for producing massive omics data, new possibilities and challenges have also emerged in different fields of biology and medicine. Dealing with such data on different scales with different scopes such as genomics, transcriptomics, proteomics and metabolomics, demands appropriate data collection, preprocessing, statistical analysis, interpretation and visualization. LÄS MER
5. Hidden patterns that matter : statistical methods for analysis of DNA and RNA data
Sammanfattning : Understanding how the genetic variations can affect characteristics and function of organisms can help researchers and medical doctors to detect genetic alterations that cause disease and reveal genes that causes antibiotic resistance. The opportunities and progress associated with such data come however with challenges related to statistical analysis. LÄS MER