life sciences data management: turning data complexity into competitive advantage

Life Sciences span from basic research on micro-organisms, plants and animals including Humans, to applied and exploratory research on living systems, not to mention Healthcare Sciences. All these approaches question a wide range of different problems that implement numerous procedures and leverage very sophisticated equipments. At the same time, digital improvments have facilitated the production of huge amount of complex data the management of which requires novel perspectives and possibly a paradigm change. A few such leads are offered here to illustrate our vision and activites in this area.

Gathering and Sharing [more]

All Standards [more]

Cross-disciplinarity [more]

Case Study - Multi-Omics Meta/Data Integration

Understanding and solving complex problems on living systems is likely to require data aggregation and integration at different levels of granularity, that is to say, performing multi-omics integration. OWe discussed our experience on Multi-Omics Data management.

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From the Blog - Computer-aided Discovery: the invisible danger

Constraints and abstractions used for turning data sets and analysis methods into computer-understandable information, introduce distorsions on computer-aided discovery and any meta/data handling must be explicited to get credible and best valuable outputs

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Selected Resource

Book on search engines

This book examines the different ways information is identifed through metadata for designing new search engines(Jouis, Biskri, Ganascia and Roux, Eds., 2012)