Big data management for information centralization (ie making data of interest findable) and
integration (ie making related data connectable) in health research is a defining challenge in …

Laboratory medicine is a digital science. Every large hospital produces a wealth of data
each day—from simple numerical results from, eg, sodium measurements to highly complex …

Background Microbial inhabitants of soils are important to ecosystem and planetary
functions, yet there are large gaps in our knowledge of their diversity and ecology. The …

Abstract While Next-Generation Sequencing (NGS) can now be considered an established
analysis technology for research applications across the life sciences, the analysis …

The wave of new technologies has opened up the opportunity for cost-effective generation of
high-throughput profiles of biological systems. This is generating tons of biological data. It is …

While the adoption of next generation sequencing has rapidly expanded, the informatics
infrastructure used to manage the data generated by this technology has not kept pace …

In the past decade, cancer research has seen an increasing trend towards high-throughput
techniques and translational approaches. The increasing availability of assays that utilise …

Translational medicine is a domain turning results of basic life science research into new
tools and methods in a clinical environment, for example, as new diagnostics or therapies …

Abstract The Big Data characteristics, namely volume, variety and velocity, currently
highlight the severe limitations of traditional Data Warehouses (DWs). Their strict relational …

Nowadays, the concept of Smart City provides a rich analytical context, highlighting the need
to store and process vast amounts of heterogeneous data flowing at different velocities. This …