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Showing 1 to 8 of 8 for “"Gene clustering"”.

  1. Exploring the boundaries of shallow phylogeny in the YESS group and the dynamics of gene cluster and operon formation in bacterial genomes

    … possible to separate such genomes into different genera, species and strains. Specifically, I addressed how different approaches such as the use of 16S rRNA phylogenetic trees, phylogenetic supertrees and concatenation of individual genes in order to construct phylogenetic trees compare with one …

    maynooth Repository record for Exploring the boundaries of shallow phylogeny in the YESS group and the dynamics of gene cluster and operon formation in bacterial genomes (opens in a new tab)

  2. Adaptive metabolic gene clusters as toolkits for chemical innovation: Investigation of the origin of the avenacin gene cluster for synthesis of defense compounds in oats

    Operon-like gene clusters are functional cassettes of physically linked and non-homologous genes involved in the same pathway. To date, 20 such plant gene clusters have been discovered, all of which are involved in specialised metabolism. Plant gene clusters raise interesting biological questions …

    east-anglia Repository record for Adaptive metabolic gene clusters as toolkits for chemical innovation: Investigation of the origin of the avenacin gene cluster for synthesis of defense compounds in oats (opens in a new tab)

  3. Computational Dissection of Composite Molecular Signatures and Transcriptional Modules

    … modeling framework with which to analyze gene expression profiling data for computational dissection of molecular signatures and transcriptional modules. The first part of the dissertation is focused on extracting pure gene expression signals from tissue or cell mixtures. The main goal of …

    vt Repository record for Computational Dissection of Composite Molecular Signatures and Transcriptional Modules (opens in a new tab)

  4. Learning Statistical and Geometric Models from Microarray Gene Expression Data

    … about disease mechanisms from microarray gene expression data. To provide a high-level overview of gene expression data for easy and insightful understanding of data structure, we propose a novel statistical data clustering and visualization algorithm that is comprehensively effective for …

    vt Repository record for Learning Statistical and Geometric Models from Microarray Gene Expression Data (opens in a new tab)

  5. Dexamethasone- and age-sensitive genes in neonatal small intestine

    … the intestine. To identify fructose-responsive genes whose expression also changes with age, intestines of 10 and 20 d old pups were perfused, by Ferraris et al., with fructose and then compared by microarray analysis. From this, a gene clustering analysis revealed that some age- and …

    njit Repository record for Dexamethasone- and age-sensitive genes in neonatal small intestine (opens in a new tab)

  6. Modeling And Identification Of Differentially Regulated Genes Using Transcriptomics And Proteomics Data

    … We try to use changes in expression levels of genes to study responses of these organisms to various environmental conditions such as availability of nutrients, concentrations of chemicals in growth media, and temperature. Three specific problems studied here are transcriptomics modifications …

    wustl Repository record for Modeling And Identification Of Differentially Regulated Genes Using Transcriptomics And Proteomics Data (opens in a new tab)

  7. Modeling transcriptomic dynamics and epigenomic conservation

    Gene regulatory networks control gene expression during various biological processes, including two sets with similarity: differentiation processes of embryonic stem (ES) cells and embryo development processes. This thesis work centers on two aspects in analyses of such gene expression patterns: …

    uiuc Repository record for Modeling transcriptomic dynamics and epigenomic conservation (opens in a new tab)

  8. Module-based Analysis of Biological Data for Network Inference and Biomarker Discovery

    … The first part of the dissertation is focused on gene module identification in gene expression data. As the most popular way to identify gene modules, many cluster algorithms have been applied to the gene expression data analysis. For the purpose of evaluating clustering algorithms from a …

    vt Repository record for Module-based Analysis of Biological Data for Network Inference and Biomarker Discovery (opens in a new tab)