Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.


GoSurfer uses Gene Ontology (GO) information to analyze gene sets obtained from genome-wide computations or microarray analyses. GoSurfer is a graphical interactive data mining tool. It associates user input genes with GO terms and visualizes such GO terms as a hierarchical tree. Users can manipulate the tree output by various means, like setting heuristic thresholds or using statistical tests. Significantly important GO terms resulted from a statistical test can be highlighted. All related information are exportable either as texts or as graphics. Platform: Windows compatible

URL: http://bioinformatics.bioen.illinois.edu/gosurfer/index.htm

Resource ID: nlx_149268     Resource Type: Resource     Version: Latest Version


gene, gene ontology, genome-wide, microarray, graph, data mining, statistical analysis, bioinformatics, genomics, gene cluster, multiple hypothesis testing, false discovery rate

Listed By

Gene Ontology Tools

Alternate URLs




Related To




Parent Organization

Additional Resource Types

Software Application


Free for academic use

Old URLs


Publication Link


Original Submitter


Version Status


Submitted On

12:00am July 13, 2012

Originated From


Changes from Previous Version

    No Changes

    Version 4

    Created 1 month ago by Christie Wang

    Version 3

    Created 2 months ago by Christie Wang

    Version 2

    Created 2 months ago by Christie Wang

    Version 1

    Created 3 years ago by Anonymous

    GoSurfer: a graphical interactive tool for comparative analysis of large gene sets in Gene Ontology space.

    • Zhong S
    • Appl. Bioinformatics
    • 2004 10

    The analysis of complex patterns of gene regulation is central to understanding the biology of cells, tissues and organisms. Patterns of gene regulation pertaining to specific biological processes can be revealed by a variety of experimental strategies, particularly microarrays and other highly parallel methods, which generate large datasets linking many genes. Although methods for detecting gene expression have improved substantially in recent years, understanding the physiological implications of complex patterns in gene expression data is a major challenge. This article presents GoSurfer, an easy-to-use graphical exploration tool with built-in statistical features that allow a rapid assessment of the biological functions represented in large gene sets. GoSurfer takes one or two list(s) of gene identifiers (Affymetrix probe set ID) as input and retrieves all the Gene Ontology (GO) terms associated with the input genes. GoSurfer visualises these GO terms in a hierarchical tree format. With GoSurfer, users can perform statistical tests to search for the GO terms that are enriched in the annotations of the input genes. These GO terms can be highlighted on the GO tree. Users can manipulate the GO tree in various ways and interactively query the genes associated with any GO term. The user-generated graphics can be saved as graphics files, and all the GO information related to the input genes can be exported as text files. AVAILABILITY: GoSurfer is a Windows-based program freely available for noncommercial use and can be downloaded at http://www.gosurfer.org. Datasets used to construct the trees shown in the figures in this article are available at http://www.gosurfer.org/download/GoSurfer.zip.