Search results for "Marker Genes"
showing 3 items of 3 documents
Neuronal activity triggers uptake of hematopoietic extracellular vesicles in vivo
2019
Communication with the hematopoietic system is a vital component of regulating brain function in health and disease. Traditionally, the major routes considered for this neuroimmune communication are by individual molecules such as cytokines carried by blood, by neural transmission, or, in more severe pathologies, by the entry of peripheral immune cells into the brain. In addition, functional mRNA from peripheral blood can be directly transferred to neurons via extracellular vesicles (EVs), but the parameters that determine their uptake are unknown. Using varied animal models that stimulate neuronal activity by peripheral inflammation, optogenetics, and selective proteasome inhibition of dop…
Detection of condition-specific marker genes from RNA-seq data with MGFR
2019
The identification of condition-specific genes is key to advancing our understanding of cell fate decisions and disease development. Differential gene expression analysis (DGEA) has been the standard tool for this task. However, the amount of samples that modern transcriptomic technologies allow us to study, makes DGEA a daunting task. On the other hand, experiments with low numbers of replicates lack the statistical power to detect differentially expressed genes. We have previously developed MGFM, a tool for marker gene detection from microarrays, that is particularly useful in the latter case. Here, we have adapted the algorithm behind MGFM to detect markers in RNA-seq data. MGFR groups s…
MGFM: a novel tool for detection of tissue and cell specific marker genes from microarray gene expression data
2015
Background Identification of marker genes associated with a specific tissue/cell type is a fundamental challenge in genetic and cell research. Marker genes are of great importance for determining cell identity, and for understanding tissue specific gene function and the molecular mechanisms underlying complex diseases. Results We have developed a new bioinformatics tool called MGFM (Marker Gene Finder in Microarray data) to predict marker genes from microarray gene expression data. Marker genes are identified through the grouping of samples of the same type with similar marker gene expression levels. We verified our approach using two microarray data sets from the NCBI’s Gene Expression Omn…