Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Feichtinger, J; McFarlane, RJ; Larcombe, LD.
CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data.
Database (Oxford). 2012; 2012(10): bas055-bas055.
Doi: 10.1093/database/bas055
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- Abstract:
- The identification of novel candidate markers is a key challenge in the development of cancer therapies. This can be facilitated by putting accessible and automated approaches analysing the current wealth of 'omic'-scale data in the hands of researchers who are directly addressing biological questions. Data integration techniques and standardized, automated, high-throughput analyses are needed to manage the data available as well as to help narrow down the excessive number of target gene possibilities presented by modern databases and system-level resources. Here we present CancerMA, an online, integrated bioinformatic pipeline for automated identification of novel candidate cancer markers/targets; it operates by means of meta-analysing expression profiles of user-defined sets of biologically significant and related genes across a manually curated database of 80 publicly available cancer microarray datasets covering 13 cancer types. A simple-to-use web interface allows bioinformaticians and non-bioinformaticians alike to initiate new analyses as well as to view and retrieve the meta-analysis results. The functionality of CancerMA is shown by means of two validation datasets.
- Find related publications in this database (using NLM MeSH Indexing)
- Access to Information -
- Automation -
- Computational Biology - methods
- Databases, Genetic -
- Gene Expression Regulation, Neoplastic -
- Humans -
- Internet -
- Meta-Analysis as Topic -
- Neoplasms - genetics
- Oligonucleotide Array Sequence Analysis -
- Reproducibility of Results -
- User-Computer Interface -
- Workflow -