Paper Info
Title
CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data.
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.
Year
DOI
Venue
2012
10.1093/database/bas055
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
Keywords
Field
DocType
automation,internet,computational biology,workflow
Data integration,Data mining,Information retrieval,Computer science,Automation,Bioinformatics,Web application,Microarray databases,User interface,Workflow,Meta-Analysis as Topic,The Internet
Journal
Volume
ISSN
Citations 
2012
1758-0463
2
PageRank 
References 
Authors
0.39
15
3
Name
Order
Citations
PageRank
Julia Feichtinger120.73
Ramsay J McFarlane220.73
Lee D Larcombe321.40