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1.  MageComet—web application for harmonizing existing large-scale experiment descriptions 
Bioinformatics  2012;28(10):1402-1403.
Motivation: Meta-analysis of large gene expression datasets obtained from public repositories requires consistently annotated data. Curation of such experiments, however, is an expert activity which involves repetitive manipulation of text. Existing tools for automated curation are few, which bottleneck the analysis pipeline.
Results: We present MageComet, a web application for biologists and annotators that facilitates the re-annotation of gene expression experiments in MAGE-TAB format. It incorporates data mining, automatic annotation, use of ontologies and data validation to improve the consistency and quality of experimental meta-data from the ArrayExpress Repository.
Availability and implementation: Source and tutorials for MageComet are openly available at goo.gl/8LQPR under the GNU GPL v3 licenses. An implementation can be found at goo.gl/IdCuA
Contact: parkinson@ebi.ac.uk or xue.vin@gmail.com
doi:10.1093/bioinformatics/bts148
PMCID: PMC3348561  PMID: 22474121
2.  Annotare—a tool for annotating high-throughput biomedical investigations and resulting data 
Bioinformatics  2010;26(19):2470-2471.
Summary: Computational methods in molecular biology will increasingly depend on standards-based annotations that describe biological experiments in an unambiguous manner. Annotare is a software tool that enables biologists to easily annotate their high-throughput experiments, biomaterials and data in a standards-compliant way that facilitates meaningful search and analysis.
Availability and Implementation: Annotare is available from http://code.google.com/p/annotare/ under the terms of the open-source MIT License (http://www.opensource.org/licenses/mit-license.php). It has been tested on both Mac and Windows.
Contact: rshankar@stanford.edu
doi:10.1093/bioinformatics/btq462
PMCID: PMC2944206  PMID: 20733062
3.  Modeling sample variables with an Experimental Factor Ontology 
Bioinformatics  2010;26(8):1112-1118.
Motivation: Describing biological sample variables with ontologies is complex due to the cross-domain nature of experiments. Ontologies provide annotation solutions; however, for cross-domain investigations, multiple ontologies are needed to represent the data. These are subject to rapid change, are often not interoperable and present complexities that are a barrier to biological resource users.
Results: We present the Experimental Factor Ontology, designed to meet cross-domain, application focused use cases for gene expression data. We describe our methodology and open source tools used to create the ontology. These include tools for creating ontology mappings, ontology views, detecting ontology changes and using ontologies in interfaces to enhance querying. The application of reference ontologies to data is a key problem, and this work presents guidelines on how community ontologies can be presented in an application ontology in a data-driven way.
Availability: http://www.ebi.ac.uk/efo
Contact: malone@ebi.ac.uk
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btq099
PMCID: PMC2853691  PMID: 20200009
4.  Importing ArrayExpress datasets into R/Bioconductor 
Bioinformatics  2009;25(16):2092-2094.
Summary:ArrayExpress is one of the largest public repositories of microarray datasets. R/Bioconductor provides a comprehensive suite of microarray analysis and integrative bioinformatics software. However, easy ways for importing datasets from ArrayExpress into R/Bioconductor have been lacking. Here, we present such a tool that is suitable for both interactive and automated use.
Availability: The ArrayExpress package is available from the Bioconductor project at http://www.bioconductor.org. A users guide and examples are provided with the package.
Contact: audrey@ebi.ac.uk
Supplementary information:Supplementary data are available Bioinformatics online.
doi:10.1093/bioinformatics/btp354
PMCID: PMC2723004  PMID: 19505942
5.  MAGETabulator, a suite of tools to support the microarray data format MAGE-TAB 
Bioinformatics  2008;25(2):279-280.
Summary: The MAGE-TAB format for microarray data representation and exchange has been proposed by the microarray community to replace the more complex MAGE-ML format. We present a suite of tools to support MAGE-TAB generation and validation, conversion between existing formats for data exchange, visualization of the experiment designs encoded by MAGE-TAB documents and the mining of such documents for semantic content.
Availability: Software is available from http://tab2mage.sourceforge.net/
Contact: tfrayner@gmail.com
doi:10.1093/bioinformatics/btn617
PMCID: PMC2638998  PMID: 19038988

Results 1-5 (5)