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Using ‘collective omics data’ for biomedical research training
Author(s) -
Chaussabel Damien,
Rinchai Darawan
Publication year - 2018
Publication title -
immunology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.297
H-Index - 133
eISSN - 1365-2567
pISSN - 0019-2805
DOI - 10.1111/imm.12944
Subject(s) - profiling (computer programming) , data science , omics , underpinning , scale (ratio) , resource (disambiguation) , visualization , computer science , bioinformatics , biology , data mining , engineering , computer network , civil engineering , physics , quantum mechanics , operating system
Summary Systems‐scale molecular profiling data accumulating in public repositories may constitute a useful resource for immunologists. It is for instance likely that information relevant to their chosen line of research be found among the more than 90,000 data series available in the NCBI Gene Expression Omnibus. Such ‘collective omics data’ may also be employed as source material for training purposes. This is the case when training curricula aim at the development of bioinformatics skills necessary for the analysis, interpretation or visualization of data generated on global scales. But ‘collective omics data’ may also be reused for training purposes to foster the development of the skills and ‘mental habits’ underpinning traditional reductionist science approaches. This review describes a small‐scale initiative involving investigators, for the most part immunologists, having engaged in a range of training activities relying on ‘collective omics data’.