CancerEST: a web-based tool for automatic meta-analysis of public EST data.
The identification of cancer-restricted biomarkers is fundamental to the development of novel cancer therapies and diagnostic tools. The construction of comprehensive profiles to define tissue- and cancer-specific gene expression has been central to this. To this end, the exploitation of the current wealth of 'omic'-scale databases can be facilitated by automated approaches, allowing researchers to directly address specific biological questions. Here we present CancerEST, a user-friendly and intuitive web-based tool for the automated identification of candidate cancer markers/targets, for examining tissue specificity as well as for integrated expression profiling. CancerEST operates by means of constructing and meta-analyzing expressed sequence tag (EST) profiles of user-supplied gene sets across an EST database supporting 36 tissue types. Using a validation data set from the literature, we show the functionality and utility of CancerEST. DATABASE URL: http://www.cancerest.org.uk.
North 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.
Julia
J
Feichtinger
Ramsay J
RJ
McFarlane
Lee D
LD
Larcombe
D019295:Computational Biology / Q000379:methods*; D003628:Database Management Systems; D030541:Databases, Genetic; D020224:Expressed Sequence Tags; D006801:Humans; D016247:Information Storage and Retrieval; D020407:Internet; D009369:Neoplasms / Q000235:genetics / Q000378:metabolism