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Updated: May 1, 2026

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CancerEST: a web-based tool for automatic meta-analysis of public EST data.

Julia Feichtinger1, Ramsay J McFarlane, Lee D Larcombe

  • 1North West Cancer Research Institute, Bangor University, Bangor, Gwynedd LL57 2UW, UK, Institute for Genomics and Bioinformatics, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria, Core Facility Bioinformatics, Austrian Centre of Industrial Biotechnology, Petersgasse 14, 8010 Graz, Austria, NISCHR Cancer Genetics Biomedical Research Unit, Bangor University, Bangor, Gwynedd LL57 2UW, UK, Liverpool Cancer Research UK Centre, University of Liverpool, Liverpool, Merseyside L3 9TA, UK and Applied Mathematics and Computing Group, Cranfield University, Cranfield, Bedfordshire MK43 0AL, UK.

Database : the Journal of Biological Databases and Curation
|April 10, 2014
PubMed
Summary

CancerEST is a new web tool that helps find cancer biomarkers by analyzing gene expression data. It aids in developing new cancer therapies and diagnostic tools.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Cancer Research

Background:

  • Identifying cancer-specific biomarkers is crucial for developing targeted therapies and diagnostics.
  • Comprehensive gene expression profiling is essential for understanding tissue and cancer specificity.
  • Automated approaches are needed to efficiently analyze large 'omic'-scale databases.

Purpose of the Study:

  • To present CancerEST, a web-based tool for automated identification of cancer markers.
  • To enable examination of tissue specificity and integrated expression profiling.
  • To facilitate the discovery of novel cancer targets and biomarkers.

Main Methods:

  • CancerEST constructs and meta-analyzes expressed sequence tag (EST) profiles.
  • It utilizes a user-supplied gene set against an EST database covering 36 tissue types.
  • The tool provides an automated approach for analyzing gene expression data.

Main Results:

  • Demonstrated the functionality and utility of CancerEST using a literature-based validation dataset.
  • Successfully identified candidate cancer markers and assessed tissue specificity.
  • Provided a user-friendly platform for integrated expression profiling.

Conclusions:

  • CancerEST is an effective tool for identifying potential cancer biomarkers and targets.
  • The tool facilitates research into tissue- and cancer-specific gene expression.
  • CancerEST supports the development of novel cancer diagnostics and therapeutics.