Data management and analysis for gene expression arrays

Olga Ermolaeva, Mohit Rastogi, Kim D. Pruitt, Gregory D. Schuler, Michael L. Bittner, Yidong Chen, Richard Simon, Paul Meltzer, Jeffrey M. Trent, Mark S. Boguski

Research output: Contribution to journalReview articlepeer-review

260 Scopus citations


Microarray technology makes it possible to simultaneously study the expression of thousands of genes during a single experiment. We have developed an information system, ArrayDB, to manage and analyse large-scale expression data. The underlying relational database was designed to allow flexibility in the nature and structure of data input and also in the generation of standard or customized reports through a web-browser interface. ArrayDB provides varied options for data retrieval and analysis tools that should facilitate the interpretation of complex hybridization results. A sampling of ArrayDB storage, retrieval and analysis capabilities is available (, along with information on a set of approximately 15,000 genes used to fabricate several widely used microarrays. Information stored in ArrayDB is used to provide integrated gene expression reports by linking array target sequences with NCBI's Entrez retrieval system, UniGene and KEGG pathway views. The integration of external information resources is essential in interpreting intrinsic patterns and relationships in large-scale gene expression data.

Original languageEnglish (US)
Pages (from-to)19-23
Number of pages5
JournalNature Genetics
Issue number1
StatePublished - 1998
Externally publishedYes

ASJC Scopus subject areas

  • Genetics


Dive into the research topics of 'Data management and analysis for gene expression arrays'. Together they form a unique fingerprint.

Cite this