Data and knowledge management in translational research: implementation of the eTRIKS platform for the IMI OncoTrack consortium

For large international research consortia, such as those funded by the European Union's Horizon 2020 programme or the Innovative Medicines Initiative, good data coordination practices and tools are essential for the successful collection, organization and analysis of the resulting data. Resear...

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Bibliographic Details
Published in:	BMC bioinformatics Vol. 20; no. 1; p. 164
Main Authors:	Gu, Wei, Yildirimman, Reha, Van der Stuyft, Emmanuel, Verbeeck, Denny, Herzinger, Sascha, Satagopam, Venkata, Barbosa-Silva, Adriano, Schneider, Reinhard, Lange, Bodo, Lehrach, Hans, Guo, Yike, Henderson, David, Rowe, Anthony
Format:	Journal Article
Language:	English
Published:	England BioMed Central Ltd 01-04-2019 BioMed Central BMC
Subjects:	Animal models Animals Biological effects Biological markers Biological materials Biological models (mathematics) Biology Biomarkers Cancer genetics Cancer therapies Cell culture Cells, Cultured Clinical medicine Cohort analysis Collaboration Colorectal cancer Computational biology Computer Simulation Consortia Data analysis Data collection Data integration Data management Data processing Databases, Factual Datasets Disease Models, Animal Diseases DNA sequencing Gene mapping Gene sequencing Genomes Genomics Humans Hypotheses Identification and classification Immunoglobulins Information management Integration Knowledge Management Lung diseases Mapping Medical research Methodology Methods Models, Biological Multiple sclerosis Oncology Precision medicine Proteomics Software Systems Biology Technology Technology application Time Translation Translational Medical Research - methods Translational medicine Translational research Translations Tumor markers Tumors Whole Genome Sequencing Xenograft Model Antitumor Assays Xenografts Xenotransplantation Europe Oncology Data management Precision medicine Translational medicine
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Summary:	For large international research consortia, such as those funded by the European Union's Horizon 2020 programme or the Innovative Medicines Initiative, good data coordination practices and tools are essential for the successful collection, organization and analysis of the resulting data. Research consortia are attempting ever more ambitious science to better understand disease, by leveraging technologies such as whole genome sequencing, proteomics, patient-derived biological models and computer-based systems biology simulations. The IMI eTRIKS consortium is charged with the task of developing an integrated knowledge management platform capable of supporting the complexity of the data generated by such research programmes. In this paper, using the example of the OncoTrack consortium, we describe a typical use case in translational medicine. The tranSMART knowledge management platform was implemented to support data from observational clinical cohorts, drug response data from cell culture models and drug response data from mouse xenograft tumour models. The high dimensional (omics) data from the molecular analyses of the corresponding biological materials were linked to these collections, so that users could browse and analyse these to derive candidate biomarkers. In all these steps, data mapping, linking and preparation are handled automatically by the tranSMART integration platform. Therefore, researchers without specialist data handling skills can focus directly on the scientific questions, without spending undue effort on processing the data and data integration, which are otherwise a burden and the most time-consuming part of translational research data analysis.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1471-2105 1471-2105
DOI:	10.1186/s12859-019-2748-y