PubMatrix: A tool for multiplex literature mining

Kevin G. Becker, Douglas A. Hosack, Glynn Dennis, Richard A. Lempicki, Tiffani J. Bright, Chris Cheadle, Jim Engel

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Molecular experiments using multiplex strategies such as cDNA microarrays or proteomic approaches generate large datasets requiring biological interpretation. Text based data mining tools have recently been developed to query large biological datasets of this type of data. PubMatrix is a web-based tool that allows simple text based mining of the NCBI literature search service PubMed using any two lists of keywords terms, resulting in a frequency matrix of term co-occurrence. Results: For example, a simple term selection procedure allows automatic pair-wise comparisons of approximately 1-100 search terms versus approximately 1-10 modifier terms, resulting in up to 1,000 pair wise comparisons. The matrix table of pair-wise comparisons can then be surveyed, queried individually, and archived. Lists of keywords can include any terms currently capable of being searched in PubMed. In the context of cDNA microarray studies, this may be used for the annotation of gene lists from clusters of genes that are expressed coordinately. An associated PubMatrix public archive provides previous searches using common useful lists of keyword terms. Conclusions: In this way, lists of terms, such as gene names, or functional assignments can be assigned genetic, biological, or clinical relevance in a rapid flexible systematic fashion.

Original languageEnglish (US)
Article number61
JournalBMC Bioinformatics
Volume4
DOIs
StatePublished - Dec 10 2003

Keywords

  • Literature mining
  • Microarray
  • Proteomic
  • PubMed

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

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