James Giovannoni
generated the gene expression data through RNA - sequencing and Lukas Mueller provided additional analysis to confirm the quality of the genome assembly.
Not exact matches
«It has taken us years to assemble the clinical outcome database and tissue samples,
generate the immunohistochemical biomarkers,
gene expression profiles and analyse the
data for this study — and we were delighted to find a definite link between alpha beta crystallin and breast cancer progression, which we hope will ultimately improve clinical outcomes.
Most of these were invalidated when challenged with experimental
data generated in Smith's laboratory, which measured
gene expression of ESCs across 23 different cell culture conditions, all of which maintained pluripotency.
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.
We find evidence of
expression for all VR, and almost all OR
genes that are annotated as functional in the reference genome, and use the
data to
generate over 1100 new, multi-exonic, significantly extended receptor
gene annotations.
To enable comparison of
gene expression in diverse bacterial species in myriad sample types and growth conditions, much of his work is dedicated to developing more robust and high - throughput methods for
generating bacterial cDNA libraries and mining bacterial RNA - Seq
data for biologically relevant trends.
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.
To annotate the genome, the team
generated transcriptome sequence
data — which can be used to measure
gene expression based on RNA levels — in 12 different tissues types.
Specifically, we have
generated clusters of transcripts that behave the same way under the entire spectrum of the sixty - seven experimental conditions; we have assembled
genes in groups according to their time of
expression during successive days of ES cell differentiation; we have included expression profiles of specific gene classes such as transcription regulatory factors and Expressed Sequence Tags; transcripts have been arranged in «Expression Waves» and juxtaposed to genes with opposite or complementary expression patterns; we have designed search engines to display the expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic
expression during successive days of ES cell differentiation; we have included
expression profiles of specific gene classes such as transcription regulatory factors and Expressed Sequence Tags; transcripts have been arranged in «Expression Waves» and juxtaposed to genes with opposite or complementary expression patterns; we have designed search engines to display the expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic
expression profiles of specific
gene classes such as transcription regulatory factors and Expressed Sequence Tags; transcripts have been arranged in «
Expression Waves» and juxtaposed to genes with opposite or complementary expression patterns; we have designed search engines to display the expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic
Expression Waves» and juxtaposed to
genes with opposite or complementary
expression patterns; we have designed search engines to display the expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic
expression patterns; we have designed search engines to display the
expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic
expression profile of any transcript during ES cell differentiation;
gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic
expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual
genes or
gene clusters of interest and links to microarray and genomic resources.