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Genomics as a service: A joint computing and networking perspective

G. Reali, M. Femminella, E. Nunzi, D. Valocchi
2018 Computer Networks  

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https://web.archive.org/web/20191026192929/https://arxiv.org/pdf/1802.05443v1.pdf

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2018 pre-print arXiv:1802.05443v1 fatcat:ftw74mawbnfwrg4jcofe5azbki

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2018 accepted
arXiv:1802.05443v2 fatcat:kepa6aqly5dpxh6aeazh5myhay
We first focus on existing service platforms, and analyze them in terms of service features, such as scalability, flexibility, and efficiency.  ...  A first contribution of this paper consists of identifying the still unexploited features of genomic data that could allow optimizing their networked management.  ...  Essentially, each base of the sequence read of the input FASTQ file is checked and filtered based on its Phred quality score, an integer value that measures the quality of the single nucleotide identification  ... 
doi:10.1016/j.comnet.2018.08.005 fatcat:w562rwbavnax7pbtairhtnadje
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G. Reali, M. Femminella, E. Nunzi, D. Valocchi. "Genomics as a service: A joint computing and networking perspective." Computer Networks (2018) 27-51

Modern Systems for Large-scale Genomics Data Analysis in the Cloud

Sergei Yakneen
2019

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Butler has been used to analyse over 725TB of DNA sequencing data on the cloud, using 1500 CPU cores, and 6TB of RAM, delivering results with 43% increased efficiency compared to other tools.  ...  Butler relies on industry-strength opensource components in order to deliver a framework that is robust and scalable to thousands of compute cores and millions of workflow executions.  ...  Acknowledgements This work is dedicated to the memory of my mother Elena Gitelson.  ... 
doi:10.11588/heidok.00027013 fatcat:excb3e7whnd6xbgilbod62wse4
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Sergei Yakneen. "Modern Systems for Large-scale Genomics Data Analysis in the Cloud." (2019)

The Role of Distributed Computing in Big Data Science: Case Studies in Forensics and Bioinformatics [article]

Gianluca Roscigno, Universita' Degli Studi Di Salerno, Universita' Degli Studi Di Salerno
2017

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The solutions such as Hadoop are attractive, since they simplify the transformation of an application from non-parallel to the distributed one by means of general utilities and without many skills.  ...  The era of Big Data is leading the generation of large amounts of data, which require storage and analysis capabilities that can be only ad- dressed by distributed computing systems.  ...  A traditional process has a single thread of control, while a multi-threading process has multiple threads of control which can perform more than one task at a time on dierent CPU cores. processors, and  ... 
doi:10.14273/unisa-725 fatcat:e3ysdvu32vhehef2fccltvqrxm
Citation

Gianluca Roscigno, Universita' Degli Studi Di Salerno, Universita' Degli Studi Di Salerno. "The Role of Distributed Computing in Big Data Science: Case Studies in Forensics and Bioinformatics." (2017)