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DNA Microarrays

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Related Experiment Video

Updated: Jun 28, 2026

Pattern-based Search of Epigenomic Data Using GeNemo

Pattern-based Search of Epigenomic Data Using GeNemo

Published on: October 8, 2017

Implementation of GenePattern within the Stanford Microarray Database.

Jeremy Hubble¹, Janos Demeter, Heng Jin

¹Department of Genetics, Stanford University School of Medicine, CA 94305, USA.

Nucleic Acids Research

|October 28, 2008

Summary

This summary is machine-generated.

The Stanford Microarray Database (SMD) now integrates GenePattern software, enhancing microarray data analysis capabilities. This open-source extension allows researchers worldwide to access new tools and share analysis pipelines.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

The Stanford Microarray Database (SMD) is a widely used platform for storing, annotating, and analyzing microarray data.
Existing SMD tools lacked a streamlined method for designing, executing, and sharing analysis pipelines, hindering publication and collaboration.

Purpose of the Study:

To integrate the GenePattern software package into the SMD codebase.
To enhance SMD's data analysis capabilities and provide a user-friendly interface for creating and sharing analysis pipelines.

Main Methods:

Incorporation of the GenePattern software package directly into the existing SMD infrastructure.
Development of a plug-in architecture within SMD to facilitate the integration and sharing of additional analysis tools.

Main Results:

SMD now offers access to a broader suite of microarray data analysis tools through GenePattern.
The integrated system simplifies the design, execution, and documentation of analysis pipelines for researchers.
The enhanced SMD is freely available under an Open Source license, enabling wider adoption and local installations.

Conclusions:

The integration of GenePattern significantly expands SMD's analytical power and usability for the research community.
This open-source extension promotes collaborative research and reproducible microarray data analysis globally.