0000000001143890

AUTHOR

Luigi Di Biasi

0000-0002-9583-6681

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Mapreduce in computational biology - A synopsis

2017

In the past 20 years, the Life Sciences have witnessed a paradigm shift in the way research is performed. Indeed, the computational part of biological and clinical studies has become central or is becoming so. Correspondingly, the amount of data that one needs to process, compare and analyze, has experienced an exponential growth. As a consequence, High Performance Computing (HPC, for short) is being used intensively, in particular in terms of multi-core architectures. However, recently and thanks to the advances in the processing of other scientific and commercial data, Distributed Computing is also being considered for Bioinformatics applications. In particular, the MapReduce paradigm, to…

BioinformaticSpark0301 basic medicineSettore INF/01 - InformaticaBioinformaticsProcess (engineering)Computer scienceComputer Science (all)Computational biologybioinformatics; distributed computing; hadoop; MapReduce; spark; computer science (all)Supercomputercomputer.software_genreDistributed computing03 medical and health sciences030104 developmental biologyExponential growthHadoopParadigm shiftMiddleware (distributed applications)Spark (mathematics)MapReducecomputer
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