top of page

Gene Expression Omnibus (GEO) Profiles

BioCodeKb - Bioinformatics Knowledgebase

GEO Profiles

Users should use this database to search for expression profiles of genes. The database stores gene expression profiles derived from curated DataSet records. Retrievals include the gene name, DataSet title, and a thumbnail image that depicts the expression values of that gene across each Sample in that DataSet. Experimental context is provided in the blocks at the foot of the charts making it possible to see immediately whether that gene is differentially expressed across experimental conditions.

Simple keyword searches work very well in this database. For example, if a user is studying the gene CREB5, it is only necessary to type “CREB5” into the GEO Profiles search box to retrieve all gene expression profile records for that gene across all DataSets.

The GEO Profiles database stores gene expression profiles derived from curated GEO DataSets. Each Profile is presented as a chart that displays the expression level of one gene across all Samples within a DataSet. Experimental context is provided in the bars along the bottom of the charts making it possible to see at a glance whether a gene is differentially expressed across different experimental conditions. Profiles have various types of links including internal links that connect genes that exhibit similar behaviour, and external links to relevant records in other NCBI databases.

GEO Profiles can be searched using many different attributes including keywords, gene symbols, gene names, GenBank accession numbers, or Profiles flagged as being differentially expressed.

While simple keyword searches work well, the ever-growing volume of data in GEO means it is increasingly necessary to use structured and filtered queries to find the most relevant data. The GEO Profiles database enables both simple and sophisticated queries to identify data of interest. Basic keyword searches can be performed alone or in combination with Boolean operators (AND, OR, NOT) to refine the search. Keyword searches with multiple parameters are structured with the following general format:

  • term[field] OPERATOR term[field]

where term is the search term, field is the search field (can be omitted to search for the term across all fields), and OPERATOR is the Boolean operator (“AND,” “OR,” “NOT” must be capitalized).

The results presented in GEO Profiles can be further filtered or refined in several ways. Clicking on the word “Advanced” under the search box displaying the original query takes the user to the “Advanced Search Builder” page where searches can be built from drop-down menus.

Regardless of how a user arrives at GEO Profiles results, either through direct searches or as a result of performing DataSet analyses, various features exist on GEO Profiles records to assist with further analysis and exploration.

Each entry in GEO Profiles displays the name of the gene and the title of the DataSet that the data are from, and additional annotation and information about the organism, Platform and probe identifier.


  1. Chromosome Neighbors: Retrieves Profiles for up to 20 of the closest-found chromosome neighbors within the same DataSet, helping identify expression data for genes within the same chromosomal region.

  2. Profile Neighbors: Retrieves Profiles with similar patterns of expression within the same DataSet, as calculated by Pearson correlation coefficients between pairs of Profiles.

  3. Sequence Neighbors: Retrieves Profiles based on BLAST nucleotide sequence similarity across all DataSets, assisting in the identification of genes representing sequence homologs and orthologs.

  4. Homologene neighbors: Retrieves Profiles that belong to the same HomoloGene group across all DataSets.

  5. Download Profile Data button: Downloads the values, experimental factors and gene annotations for each Profile on the page.

  6. Find Pathways button: Maps the Profiles to a frequency weighted list of pathways in NCBI’s BioSystems database.


Need to learn more about Gene Expression Omnibus (GEO) Profiles and much more?

To learn Bioinformatics, analysis, tools, biological databases, Computational Biology, Bioinformatics Programming in Python & R through interactive video courses and tutorials, Join BioCode.

bottom of page