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An interactive database of cocaine-responsive gene expression.

Willard M Freeman1, Kathryn E Dougherty, Sally E Vacca

  • 1Center for the Neurobiological Investigation of Drug Abuse, Department of Physiology and Pharmacology, Wake Forest University School of Medicine, Medical Center Blvd., Winston-Salem, NC 27157-1083, USA. freemanw@ohsu.edu

Thescientificworldjournal
|June 14, 2003
PubMed
Summary
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Scientists created a database for cocaine-induced gene expression changes, simplifying research. This tool organizes findings by brain region and gene function, aiding new hypothesis generation in drug abuse studies.

Area of Science:

  • Neuroscience
  • Genomics
  • Pharmacology

Background:

  • The postgenomic era generates vast gene expression data, often scattered across journals.
  • Drug abuse researchers face challenges with laborious literature searches for cocaine-mediated gene expression changes.

Purpose of the Study:

  • To create an interactive, user-friendly database consolidating cocaine-mediated gene expression findings.
  • To organize gene expression changes by neuroanatomical region, general function, and gene name.

Main Methods:

  • Developed a Flash-based, interactive database integrated into a webpage.
  • Included only statistically significant changes in mRNA or protein expression post-cocaine administration.
  • Provided gene descriptions, links to original publications, and OMIM entries.

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Main Results:

  • Consolidated information on cocaine-induced gene expression changes into an accessible format.
  • Organized data by neuroanatomical region, gene function, and gene name for efficient retrieval.
  • Facilitated access to original research and genetic information via integrated links.

Conclusions:

  • The database simplifies access to complex gene expression data for drug abuse researchers.
  • Enables rapid hypothesis generation for understanding cocaine abuse's physiological and behavioral impacts.
  • The organizational method is adaptable for other scientific fields dealing with large datasets.