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2024 | OriginalPaper | Buchkapitel

12. Big Data Analytics in Bioinformatics

verfasst von : Ümit Demirbaga, Gagangeet Singh Aujla, Anish Jindal, Oğuzhan Kalyon

Erschienen in: Big Data Analytics

Verlag: Springer Nature Switzerland

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Abstract

This chapter introduces the intricate interplay between big data analytics and bioinformatics, providing a comprehensive perspective on leveraging large-scale genomic data. Delving into the challenges posed by big data in bioinformatics, the narrative unfolds to explore frameworks tailored for managing extensive genomic datasets and the pivotal role of biological databases. The core focus is applying big data analytics in bioinformatics, spanning the employment of Hadoop, MapReduce, and deep learning methodologies. A detailed case study exemplifies the practical implementation of variant detection in genomes, illustrating processes like data copying to HDFS, MapReduce-based data processing, and the multistep intricacies of variant calling and interpretation. This chapter serves as a roadmap by navigating the synergy between cutting-edge analytics and the intricate nuances of bioinformatics.

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Titel: Big Data Analytics in Bioinformatics
verfasst von: Ümit Demirbaga
Gagangeet Singh Aujla
Anish Jindal
Oğuzhan Kalyon
Verlag: Springer Nature Switzerland
Buch: Big Data Analytics
Print ISBN: 978-3-031-55638-8

Electronic ISBN: 978-3-031-55639-5

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-3-031-55639-5_12

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