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    The Stem Cell Commons: an exemplar for data integration in the biomedical domain driven by the ISA framework.
    AMIA Jt Summits Transl Sci Proc 2013 18;2013:70. Epub 2013 Mar 18.
    Harvard School of Public Health, Biostatistics, Boston, MA, USA ; Harvard Stem Cell Institute, Cambridge, MA, USA.
    Comparisons of stem cell experiments at both molecular and semantic levels remain challenging due to inconsistencies in results, data formats, and descriptions among biomedical research discoveries. The Harvard Stem Cell Institute (HSCI) has created the Stem Cell Commons (, an open, community-based approach to data sharing. Experimental information is integrated using the Investigation-Study-Assay tabular format (ISA-Tab) used by over 30 organizations (ISA Commons, The early adoption of this format permitted the novel integration of three independent systems to facilitate stem cell data storage, exchange and analysis: the Blood Genomics Repository, the Stem Cell Discovery Engine, and the new Refinery platform that links the Galaxy analytical engine to data repositories.

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    linkedISA: semantic representation of ISA-Tab experimental metadata.
    BMC Bioinformatics 2014 27;15 Suppl 14:S4. Epub 2014 Nov 27.
    Background: Reporting and sharing experimental metadata- such as the experimental design, characteristics of the samples, and procedures applied, along with the analysis results, in a standardised manner ensures that datasets are comprehensible and, in principle, reproducible, comparable and reusable. Furthermore, sharing datasets in formats designed for consumption by humans and machines will also maximize their use. The Investigation/Study/Assay (ISA) open source metadata tracking framework facilitates standards-compliant collection, curation, visualization, storage and sharing of datasets, leveraging on other platforms to enable analysis and publication. Read More
    The Stem Cell Discovery Engine: an integrated repository and analysis system for cancer stem cell comparisons.
    Nucleic Acids Res 2012 Jan 24;40(Database issue):D984-91. Epub 2011 Nov 24.
    Department of Biostatistics, HSPH Bioinformatics Core, Harvard School of Public Health, Boston, MA, USA.
    Mounting evidence suggests that malignant tumors are initiated and maintained by a subpopulation of cancerous cells with biological properties similar to those of normal stem cells. However, descriptions of stem-like gene and pathway signatures in cancers are inconsistent across experimental systems. Driven by a need to improve our understanding of molecular processes that are common and unique across cancer stem cells (CSCs), we have developed the Stem Cell Discovery Engine (SCDE)-an online database of curated CSC experiments coupled to the Galaxy analytical framework. Read More
    ISA-TAB-Nano: a specification for sharing nanomaterial research data in spreadsheet-based format.
    BMC Biotechnol 2013 Jan 14;13. Epub 2013 Jan 14.
    1Knowledge Discovery and Informatics, Pacific Northwest National Laboratory, Richland, WA 99352, USA.
    Background And Motivation: The high-throughput genomics communities have been successfully using standardized spreadsheet-based formats to capture and share data within labs and among public repositories. The nanomedicine community has yet to adopt similar standards to share the diverse and multi-dimensional types of data (including metadata) pertaining to the description and characterization of nanomaterials. Owing to the lack of standardization in representing and sharing nanomaterial data, most of the data currently shared via publications and data resources are incomplete, poorly-integrated, and not suitable for meaningful interpretation and re-use of the data. Read More
    The Risa R/Bioconductor package: integrative data analysis from experimental metadata and back again.
    BMC Bioinformatics 2014 10;15 Suppl 1:S11. Epub 2014 Jan 10.
    Background: The ISA-Tab format and software suite have been developed to break the silo effect induced by technology-specific formats for a variety of data types and to better support experimental metadata tracking. Experimentalists seldom use a single technique to monitor biological signals. Providing a multi-purpose, pragmatic and accessible format that abstracts away common constructs for describing Investigations, Studies and Assays, ISA is increasingly popular. Read More