A gene expression/molecular abundance repository and a curated, online resource for gene expression data
Tutorial and training materials by OpenHelix
|Learn to use the Gene Expression Omnibus, or GEO, which is a valuable resource designed to store high-throughput gene expression and molecular abundance data. GEO acts as a repository for the data, and provides interfaces to search, retrieve, and display a wealth of information about genes in many species. This includes microarray data and many other high-throughput techniques. GEO is one of the many useful resources supported by the National Center for Biotechnology Information, or NCBI.|
- efficient ways to query GEO for specific genes or experimental designs
- how to navigate through GEO output displays to find the specific information you want
- how to navigate GEO
Recent BioMed Central research articles citing this resource
Liu Xiaoqing et al., Identification and functional characterization of bidirectional gene pairs and their intergenic regions in maize Plant genomics. BMC Genomics (2014) doi:10.1186/1471-2164-15-338
Romao Moura Josue et al., MicroRNAs in bovine adipogenesis: genomic context, expression and function Non-human and non-rodent vertebrate genomics. BMC Genomics (2014) doi:10.1186/1471-2164-15-137
Vitting-Seerup Kristoffer et al., spliceR: an R package for classification of alternative splicing and prediction of coding potential from RNA-seq data Transcriptome analysis. BMC Bioinformatics (2014) doi:10.1186/1471-2105-15-81
Fatima Attia et al., Alterations in hepatic miRNA expression during negative energy balance in postpartum dairy cattle Non-human and non-rodent vertebrate genomics. BMC Genomics (2014) doi:10.1186/1471-2164-15-28
Fu Shih-Feng et al., Transcriptome profiling of genes and pathways associated with arsenic toxicity and tolerance in Arabidopsis Plant-abiotic interactions. BMC Plant Biology (2014) doi:10.1186/1471-2229-14-94
More about the resource:
GEO can be browsed or queried in several ways, including basic searches, advanced searches, and using nucleotide sequences to begin a search. GEO contains information about platforms, data series, samples, and more. Analysis tools including clustering features are available. Learning to mine the GEO data will provide the researcher with copious amounts of information about their species, tissues, or genes of interest.
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