Search for dissertations about: "gene abundance data"

Showing result 1 - 5 of 58 swedish dissertations containing the words gene abundance data.

  2. 1. Statistical modelling and analyses of DNA sequence data with applications to metagenomics

    Author : Mariana Buongermino Pereira; Göteborgs universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; generalised hidden Markov models; gene abundance data; metagenomics; statistical modelling; bioinformatics; normalisation; DNA sequence data; bioinformatics;

    Abstract : 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. READ MORE

  4. 2. Statistical analysis of metagenomic data

    Author : Viktor Jonsson; Göteborgs universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Metagenomics; Statistical methods; Hierarchical Bayesian models; Statistical power; False discovery rate; Environmental genomics; Generalized linear models; Count data; Environmental genomics;

    Abstract : 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. READ MORE

  5. 3. Modeling of bacterial DNA patterns important in horizontal gene transfer using stochastic grammars

    Author : Mariana Buongermino Pereira; Göteborgs universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Stochastic context-free grammars; hidden Markov model; conditional random fields; integrons; attC sites; secondary structure.; secondary structure.;

    Abstract : 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. READ MORE

  6. 4. Omics Data Analysis of Complex Diseases and Traits

    Author : Saman Hosseini Ashtiani; Arne Elofsson; Dirk Repsilber; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Omics data; RNA-seq; Microarrays; Metabolomics; Network analysis; Psoriasis; E. coli; Hip osteoporosis; Lung adenocarcinoma; Spearman s correlation coefficient; LC-MS; PCA; DEG; PPI; biokemi med inriktning mot bioinformatik; Biochemistry towards Bioinformatics;

    Abstract : 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. READ MORE

  7. 5. Hidden patterns that matter : statistical methods for analysis of DNA and RNA data

    Author : Therese Kellgren; Patrik Rydén; Sara Sjöstedt de Luna; Rebecka Jörnsten; Umeå universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Genome; Next-generation sequence; statistics; microarrays; bacteria; antibiotic resistance; inherited diseases; Co-expression networks; centralization within subgroups;

    Abstract : 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. READ MORE