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
Ram Kumar Mohan Ram et al., ΔNp63α enhances the oncogenic phenotype of osteosarcoma cells by inducing the expression of GLI2 Cell and molecular biology. BMC Cancer (2014) doi:10.1186/1471-2407-14-559
Ling HT Maurice et al., A predictor for predicting Escherichia coli transcriptome and the effects of gene perturbations Networks analysis. BMC Bioinformatics (2014) doi:10.1186/1471-2105-15-140
Li Jisheng et al., MicroRNA expression profiling of the fifth-instar posterior silk gland of Bombyx mori Multicellular invertebrate genomics. BMC Genomics (2014) doi:10.1186/1471-2164-15-410
LaCroix Bonnie et al., Integrative analyses of genetic variation, epigenetic regulation, and the transcriptome to elucidate the biology of platinum sensitivity Transcriptomic methods. BMC Genomics (2014) doi:10.1186/1471-2164-15-292
Bandara Veronika et al., Hypoxia represses microRNA biogenesis proteins in breast cancer cells Cell and molecular biology. BMC Cancer (2014) doi:10.1186/1471-2407-14-533
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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