Not exact matches
By combining salivary
gene expression profiles, postconceptional age and sex, this predictive model not only assessed the probability of feeding success, but also, and most importantly, highlighted
specific developmental pathways that were likely contributing to feeding immaturity.
The patterns of these polymorphic
genes and their
expression profiles comprise the molecular signatures of unique pathophenotypes, offering the promise of diagnostic, prognostic, and therapeutic specificity; the definition of disease becomes «personalized», as does its
specific therapeutic targets.
Resident macrophages from the same lineage, such as liver Kupffer cells, brain microglia, epidermal Langerhans cells, lung alveolar macrophages..., display tissue -
specific phenotypes, perform tissue -
specific functions and have distinct
gene expression profiles.
Unfortunately, direct comparisons of
gene expression profiles obtained in independent, publicly available microarray experiments are typically compromised by substantial, experiment -
specific biases.
These include: a) Global Clusters that consist of a small, tight subset of
genes that are co-expressed under the entire spectrum of experimental conditions; b) Time Series of
gene expression profiles during successive days of standard ES cell differentiation; c) Specific Gene Classes based on hierarchical clustering of transcriptional factors and ESTs; d) Expression Waves of genes with characteristic expression profiles during ES cell differentiation, juxtaposed to waves of genes that behave in the exact opposite way; e) Pathway Animations that illustrate dynamic changes in the components of individual KEGG signaling and metabolic pathways viewed in time - related manner; and, f) Search Engines to display the expression pattern of any transcript, or groups of transcripts, during the course of ES cell differentiation, or to query the association of candidate genes with various FunGenES database clust
gene expression profiles during successive days of standard ES cell differentiation; c) Specific Gene Classes based on hierarchical clustering of transcriptional factors and ESTs; d) Expression Waves of genes with characteristic expression profiles during ES cell differentiation, juxtaposed to waves of genes that behave in the exact opposite way; e) Pathway Animations that illustrate dynamic changes in the components of individual KEGG signaling and metabolic pathways viewed in time - related manner; and, f) Search Engines to display the expression pattern of any transcript, or groups of transcripts, during the course of ES cell differentiation, or to query the association of candidate genes with various FunGenES database
expression profiles during successive days of standard ES cell differentiation; c)
Specific Gene Classes based on hierarchical clustering of transcriptional factors and ESTs; d) Expression Waves of genes with characteristic expression profiles during ES cell differentiation, juxtaposed to waves of genes that behave in the exact opposite way; e) Pathway Animations that illustrate dynamic changes in the components of individual KEGG signaling and metabolic pathways viewed in time - related manner; and, f) Search Engines to display the expression pattern of any transcript, or groups of transcripts, during the course of ES cell differentiation, or to query the association of candidate genes with various FunGenES database clust
Gene Classes based on hierarchical clustering of transcriptional factors and ESTs; d)
Expression Waves of genes with characteristic expression profiles during ES cell differentiation, juxtaposed to waves of genes that behave in the exact opposite way; e) Pathway Animations that illustrate dynamic changes in the components of individual KEGG signaling and metabolic pathways viewed in time - related manner; and, f) Search Engines to display the expression pattern of any transcript, or groups of transcripts, during the course of ES cell differentiation, or to query the association of candidate genes with various FunGenES database
Expression Waves of
genes with characteristic
expression profiles during ES cell differentiation, juxtaposed to waves of genes that behave in the exact opposite way; e) Pathway Animations that illustrate dynamic changes in the components of individual KEGG signaling and metabolic pathways viewed in time - related manner; and, f) Search Engines to display the expression pattern of any transcript, or groups of transcripts, during the course of ES cell differentiation, or to query the association of candidate genes with various FunGenES database
expression profiles during ES cell differentiation, juxtaposed to waves of
genes that behave in the exact opposite way; e) Pathway Animations that illustrate dynamic changes in the components of individual KEGG signaling and metabolic pathways viewed in time - related manner; and, f) Search Engines to display the
expression pattern of any transcript, or groups of transcripts, during the course of ES cell differentiation, or to query the association of candidate genes with various FunGenES database
expression pattern of any transcript, or groups of transcripts, during the course of ES cell differentiation, or to query the association of candidate
genes with various FunGenES database clusters.
Saturday, Oct. 21, 11:20 - 11:40 a.m., South Hall B, South Building Featured Plenary Abstract: Massively parallel reporter assays combined with cell - type
specific expression quantitative trait loci
profiling identified a functional melanoma risk variant in HIV - 1 inhibitor
gene, MX2 J. Choi, National Cancer Institute, et al
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.