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001-es BibID:	bibEBI00026091
035-os BibID:	(WoS)000503370800015 (Scopus)85077847119
Első szerző:	Tóth Ádám (mérnökinformatikus)
Cím:	Optimization of hadoop cluster for analyzing large-scale sequence data in bioinformatics / Ádám Tóth, Ramin Karimi
Dátum:	2019
ISSN:	1787-5021 1787-6117
Megjegyzések:	Unexpected growth of high-throughput sequencing platforms in recent years impacted virtually all areas of modern biology. However, the ability to produce data continues to outpace the ability to analyze them. Therefore, continuous efforts are also needed to improve bioinformatics applications for a better use of these research opportunities. Due to the complexity and diversity of metagenomics data, it has been a major challenging field of bioinformatics. Sequence-based identification methods such as using DNA signature (unique k-mer) are the most recent popular methods of real-time analysis of raw sequencing data. DNA signature discovery is compute-intensive and time-consuming. Hadoop, the application of parallel and distributed computing is one of the popular applications for the analysis of large scale data in bioinformatics. Optimization of the time-consumption and computational resource usages such as CPU consumption and memory usage are the main goals of this paper, along with the management of the Hadoop cluster nodes.
Tárgyszavak:	Természettudományok Matematika- és számítástudományok idegen nyelvű folyóiratközlemény hazai lapban folyóiratcikk hadoop optimization next-Generation Sequencing DNA signature resource management
Megjelenés:	Annales Mathematicae et Informaticae. - 50 (2019), p. 187-202. -
További szerzők:	Karimi, Ramin (1975-) (programtervező matematikus)
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