scholarly journals AtCAST3.0 Update: A Web-Based Tool for Analysis of Transcriptome Data by Searching Similarities in Gene Expression Profiles

2014 ◽  
Vol 56 (1) ◽  
pp. e7-e7 ◽  
Author(s):  
Yusuke Kakei ◽  
Yukihisa Shimada
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Transcriptome Data ◽  
Web Based

scholarly journals Meta-Analysis of Hypoxic Transcriptomes from Public Databases

Biomedicines ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 10 ◽  
Author(s):  
Hidemasa Bono ◽  
Kiichi Hirota
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Data Driven ◽  
Transcriptome Data ◽  
Rna Seq ◽  
Experimental Conditions ◽  
Oxygen Homeostasis ◽  
Before And After

Hypoxia is the insufficiency of oxygen in the cell, and hypoxia-inducible factors (HIFs) are central regulators of oxygen homeostasis. In order to obtain functional insights into the hypoxic response in a data-driven way, we attempted a meta-analysis of the RNA-seq data from the hypoxic transcriptomes archived in public databases. In view of methodological variability of archived data in the databases, we first manually curated RNA-seq data from appropriate pairs of transcriptomes before and after hypoxic stress. These included 128 human and 52 murine transcriptome pairs. We classified the results of experiments for each gene into three categories: upregulated, downregulated, and unchanged. Hypoxic transcriptomes were then compared between humans and mice to identify common hypoxia-responsive genes. In addition, meta-analyzed hypoxic transcriptome data were integrated with public ChIP-seq data on the known human HIFs, HIF-1 and HIF-2, to provide insights into hypoxia-responsive pathways involving direct transcription factor binding. This study provides a useful resource for hypoxia research. It also demonstrates the potential of a meta-analysis approach to public gene expression databases for selecting candidate genes from gene expression profiles generated under various experimental conditions.

scholarly journals ImmuneRegulation: A web-based tool for identifying human immune regulatory elements

2018 ◽  
Author(s):  
Selim Kalayci ◽  
Myvizhi Esai Selvan ◽  
Irene Ramos ◽  
Chris Cotsapas ◽  
Ruth R. Montgomery ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Regulatory Elements ◽  
Future Application ◽  
Transcriptional Responses ◽  
Web Based ◽  
Phenotypic Differences ◽  
Transcriptome Regulation

ABSTRACTHumans can vary considerably in their healthy immune phenotypes and in their immune responses to various stimuli. We have developed an interactive web-based tool, ImmuneRegulation, to enable discovery of human regulatory elements that drive some of the phenotypic differences observed in gene expression profiles. ImmuneRegulation currently provides the largest centrally integrated resource available in the literature on transcriptome regulation in whole blood and blood cell types, including genotype data from 23,040 individuals, with associated gene expression data from 30,562 experiments, that provide genetic variant-gene expression associations on ∼200 million eQTLs. In addition, it includes 14 million transcription factor (TF) binding region hits extracted from 1945 TF ChIP-seq peaks and the latest GWAS catalog of 67,230 published SNP-trait associations. Users can interactively explore ImmuneRegulation to visualize and discover associations between their gene(s) of interest and their regulators (genetic variants or transcription factors) across multiple cohorts and studies. These regulators can explain cohort or cell type dependent gene expression variations and may be critical in selecting the ideal cohorts or cell types for follow-up studies. Overall, ImmuneRegulation aims to contribute to our understanding of the effects of eQTLs and TFs on heterogeneous transcriptional responses reported in studies on the blood; in the development of molecular signatures of immune response; and facilitate their future application in patient management. ImmuneRegulation is freely available at http://icahn.mssm.edu/immuneregulation.

scholarly journals PulmonDB: a curated lung disease gene expression database

2019 ◽  
Author(s):  
Ana B. Villaseñor-Altamirano ◽  
Marco Moretto ◽  
Alejandra Zayas-Del Moral ◽  
Mariel Maldonado ◽  
Adrián Munguía-Reyes ◽  
...  
Keyword(s):  
Gene Expression ◽  
Disease Gene ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Web Based ◽  
Public Repositories ◽  
New Hypothesis ◽  
Different Sources

ABSTRACTChronic Obstructive Pulmonary Disease (COPD) and Idiopathic Pulmonary Fibrosis (IPF) have contrasting clinical and pathological characteristics, and interesting whole-genome transcriptomic profiles. However, data from public repositories are difficult to reprocess and reanalyze. Here we present PulmonDB, a web-based database (http://pulmondb.liigh.unam.mx/) and R library that facilitates exploration of gene expression profiles for these diseases by integrating transcriptomic data and curated annotation from different sources. We demonstrated the value of this resource by presenting the expression of already well-known genes of COPD and IPF across multiple experiments and the results of two differential expression analyses in which we successfully identified differences and similarities. With this first version of PulmonDB, we create a new hypothesis and compare the two diseases from a transcriptomics perspective.

scholarly journals Meta-analysis of hypoxic transcriptomes from public databases

2018 ◽  
Author(s):  
Hidemasa Bono ◽  
Kiichi Hirota
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Data Driven ◽  
Transcriptome Data ◽  
Rna Seq ◽  
Experimental Conditions ◽  
Oxygen Homeostasis ◽  
Before And After

AbstractHypoxia is the insufficiency of oxygen in the cell, and hypoxia-inducible factors (HIFs) are central regulators of oxygen homeostasis. In order to obtain functional insights into the hypoxic response in a data-driven way, we attempted a meta-analysis of the RNA-seq data from the hypoxic transcriptomes archived in public databases. In view of methodological variability of archived data in the databases, we first manually curated RNA-seq data from appropriate pairs of transcriptomes before and after hypoxic stress. These included 128 human and 52 murine transcriptome pairs. We classified the results of experiments for each gene into three categories: upregulated, downregulated, and unchanged. Hypoxic transcriptomes were then compared between humans and mice to identify common hypoxia-responsive genes. In addition, meta-analyzed hypoxic transcriptome data were integrated with public ChIP-seq data on the known human HIFs HIF-1 and HIF-2 to provide insights into hypoxia-responsive pathways involving direct transcription factor binding. This study provides a useful resource for hypoxia research. It also demonstrates the potential of a meta-analysis approach to public gene expression databases for selecting candidate genes from gene expression profiles generated under various experimental conditions.

scholarly journals SaVanT: a web-based tool for the sample-level visualization of molecular signatures in gene expression profiles

BMC Genomics ◽  
2017 ◽  
Vol 18 (1) ◽  
Author(s):  
David Lopez ◽  
Dennis Montoya ◽  
Michael Ambrose ◽  
Larry Lam ◽  
Leah Briscoe ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Molecular Signatures ◽  
Web Based

scholarly journals ArraySearch: A Web-Based Genomic Search Engine

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Tyler J. Wilson ◽  
Steven X. Ge
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Large Body ◽  
Gene Expression Profiles ◽  
Expression Data ◽  
Search Query ◽  
Web Based ◽  
The Public ◽  
Statistical Correlations ◽  
Genomic Search

Recent advances in microarray technologies have resulted in a flood of genomics data. This large body of accumulated data could be used as a knowledge base to help researchers interpret new experimental data. ArraySearch finds statistical correlations between newly observed gene expression profiles and the huge source of well-characterized expression signatures deposited in the public domain. A search query of a list of genes will return experiments on which the genes are significantly up- or downregulated collectively. Searches can also be conducted using gene expression signatures from new experiments. This resource will empower biological researchers with a statistical method to explore expression data from their own research by comparing it with expression signatures from a large public archive.

1327: Gene Expression Profiles in Benign Prostatic Hyperplasia

2004 ◽  
Vol 171 (4S) ◽  
pp. 349-350
Author(s):  
Gaelle Fromont ◽  
Michel Vidaud ◽  
Alain Latil ◽  
Guy Vallancien ◽  
Pierre Validire ◽  
...  
Keyword(s):  
Gene Expression ◽  
Benign Prostatic Hyperplasia ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Prostatic Hyperplasia
Sign in / Sign up

Export Citation Format

Share Document