Sentences with phrase «gene expression data analysis»

Inspired by the knowledge - based analysis methods developed for gene expression data analysis, we implemented methods for examining functionally - related SNPs as a group.

He group is also interested in high throughput gene expression data analysis, especially using Bayesian network (BN) approaches.

Computational genomics includes: bio-sequence analysis, gene expression data analysis, phylogenetic analysis, and more specifically pattern recognition and analysis problems such as gene finding, motif finding, gene function prediction, fusion of sequence and expression information, and evolutionary models.

Biomolecular model based on the gene expression data analyses support the reduction of glucose molecules (blue gradient) and acid buildup (gold gradient) proposed to occur in the boundary layer around the cell.

Not exact matches

Scientists from the Biogerontology Research Foundation (BGRF), a UK - based charity founded to support aging research and address the challenges of a rapidly aging population, propose a new concept for signalome - wide analysis of changes in intracellular pathways, called OncoFinder, which allows for accurate and robust cross-platform analysis of gene expression data.

At the nucleic acid level, understanding the precise regulation of genes through analysis of gene expression data will be of utmost importance.

MEGENA (for Multiscale Embedded Gene Co-expression Network Analysis) projects gene expression data onto a three dimensional sphere, allowing scientists to study hierarchical organization patterns in complex networks that are characteristic of diseases such as cancer, obesity, and AlzheimeGene Co-expression Network Analysis) projects gene expression data onto a three dimensional sphere, allowing scientists to study hierarchical organization patterns in complex networks that are characteristic of diseases such as cancer, obesity, and Alzheimegene expression data onto a three dimensional sphere, allowing scientists to study hierarchical organization patterns in complex networks that are characteristic of diseases such as cancer, obesity, and Alzheimer's.

The second tool, SuperExactTest, establishes the very first theoretical framework for assessing the statistical significance of multi-set intersections and enables users to compare very large sets of data, such as gene sets produced from genome - wide association studies (GWAS) and differential expression analysis.

A: Sheltzer: Professionally, we're working on a paper together using Joan's data - analysis ability to parse through gene - expression data from more than 20,000 cancer patients.

Evan Paull, a graduate student in Stuart's lab at UC Santa Cruz (now at Columbia University), led the computational analyses, which involved integrating the phosphoproteomic data with genomic and gene expression datasets to provide a unified view of the activated signaling pathways in late stage prostate cancer.

In the current study, prediction analysis of gene expression data was implemented in order to identify the genes that are most useful to determine the state of cyclic changes in locomotor activity.

In the current study, the researchers used infradian cyclic locomotor activity in the mutant mice as a proxy for mood - associated changes, and examined their molecular basis in the brain by conducting prediction analyses of the gene expression data.

For expression analysis in mice, we used microarray data as described above to select two internal control genes, cyclophilin B (Cphn2) and ribosomal protein S3 (Rps3).

The authors next took 997 tumors in the discovery set, integrated copy number and gene expression data, and performed clustering analyses to identify subgroups of tumors with distinct features and clinical outcomes.

James Giovannoni generated the gene expression data through RNA - sequencing and Lukas Mueller provided additional analysis to confirm the quality of the genome assembly.

Gene Set Enrichment Analysis (GSEA) is a microarray data - mining technique used to determine whether there is coordinated differential expression or «enrichment» in a set of functionally related genes when comparing control and experimental samples [35].

Bethesda, USA (2016 - present) Research areas: Super-resolution microscopy, single - molecule imaging, gene expression, computational modeling and data analysis This section includes all projects during my postdoctoral research stay at the National Institutes of Health in Bethesda, MD (Unites States): (9) Understanding gene expression in eukaryotic cells»

We have developed new BN algorithms and tools for analysis of gene interaction networks using high throughput gene expression data.

We applied gene set enrichment analysis (GSEA)(23) to expression array data using KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways.

Much of the research carried out today on rodent models generates high resolution image data, allowing characterization and analysis of brain molecular distribution, gene expression, and connectivity.

The idea behind our work in bioinformatics is to build on existing methodologies regarding large - scale data analysis and to develop novel algorithms for processing and merging complex biological data from multiple sources such as gene expression data, sequence information, protein - to - protein interaction data, clinico - pathological data etc..

The researchers found 77 women with matched imaging and gene expression data, so they combined their analyses of visceral fat and glycolysis.

These techniques and functional analysis of the resulting data revealed a number of up - and down - regulated proteins and mRNAs; i.e., up - regulated by a signal (originating internal or external to the cell) that results in increased expression of one or more genes and as a result the protein (s) encoded by those genes, and down - regulated by a process resulting in decreased gene and corresponding protein expression.

Dr Gilchrist said: «This study suggests that we may improve significantly on the widely used analysis methods for determining gene expression levels from high throughput sequence data: absolute quantitation offers a much sounder basis for determining changes in gene expression level, a measure widely used to determine the consequence of genetic, chemical or physical disturbances in living systems.»

There's also a lot of work under way for TCGA, not just the 6K capture project, but also adjunct analyses of gene expression, DNA copy number, microRNA, and DNA methylation data being generated on TCGA samples.

In brief, 330 of 364 genes, tested by quantitative or conventional PCR, gave comparable expression patterns to the data obtained by microarray analysis.

Designed and supervised the global analysis of the FunGenES gene expression profiling data and wrote the manuscript draft: AKH.

We combine biochemical, structural, cellular and functional information using purified proteins, mutant and transgenic plants, yeast and chemical genomic screening systems, transient gene expression assays, confocal microscopy and in silico data analysis to compare ROP - centered kinase signaling during cell polarity (in vitro pollen tubes), morphogenesis (whole plant) and pathogenesis (fungi - infected cells).

Provided data analysis that included statistics package development with staff statisticians, and high throughput assay advent and development (immediate early gene expression); Taq - man primer - probe research and design using primer express.