Brief. Bioinformatics - Survey of MapReduce frame operation in bioinformatics.

Tópicos

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{ age(1611) year(1155) adult(843) }
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Resumo

Bioinformatics is challenged by the fact that traditional analysis tools have difficulty in processing large-scale data from high-throughput sequencing. The open source Apache Hadoop project, which adopts the MapReduce framework and a distributed file system, has recently given bioinformatics researchers an opportunity to achieve scalable, efficient and reliable computing performance on Linux clusters and on cloud computing services. In this article, we present MapReduce frame-based applications that can be employed in the next-generation sequencing and other biological domains. In addition, we discuss the challenges faced by this field as well as the future works on parallel computing in bioinformatics.

Resumo Limpo

bioinformat challeng fact tradit analysi tool difficulti process largescal data highthroughput sequenc open sourc apach hadoop project adopt mapreduc framework distribut file system recent given bioinformat research opportun achiev scalabl effici reliabl comput perform linux cluster cloud comput servic articl present mapreduc framebas applic can employ nextgener sequenc biolog domain addit discuss challeng face field well futur work parallel comput bioinformat

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