TY - JOUR
T1 - MiMiR - An integrated platform for microarray data sharing, mining and analysis
AU - Tomlinson, Chris
AU - Thimma, Manjula
AU - Alexandrakis, Stelios
AU - Castillo, Tito
AU - Dennis, Jayne L.
AU - Brooks, Anthony
AU - Bradley, Thomas
AU - Turnbull, Carly
AU - Blaveri, Ekaterini
AU - Barton, Geraint
AU - Chiba, Norie
AU - Maratou, Klio
AU - Soutter, Pat
AU - Aitman, Tim
AU - Game, Laurence
N1 - Funding Information:
The authors acknowledge funding from the Medical Research Council, the Department of Health (NEAT), the BBSRC (BEP), and the European Union (EURATools). We thank the NEAT Management Group and Consumer Advisory Group and in particular Lady Sarah Riddle, Prof Hani Gabra, Prof Junia Melo and other clinical collaborators at the Hammersmith Hospital. We are grateful to Dr Helen Causton and Dr Jonathan Mangion for helpful discussions and comments, and to the Microarray Centre users for providing feedback on using MiMiR.
PY - 2008/9/18
Y1 - 2008/9/18
N2 - Background: Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. Results: A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. Conclusion: The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other - omics technologies.
AB - Background: Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. Results: A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. Conclusion: The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other - omics technologies.
UR - http://www.scopus.com/inward/record.url?scp=54849436647&partnerID=8YFLogxK
U2 - 10.1186/1471-2105-9-379
DO - 10.1186/1471-2105-9-379
M3 - Article
C2 - 18801157
AN - SCOPUS:54849436647
SN - 1471-2105
VL - 9
JO - BMC BIOINFORMATICS
JF - BMC BIOINFORMATICS
M1 - 379
ER -