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      Cryfa: a secure encryption tool for genomic data

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      , ,
      Bioinformatics
      Oxford University Press

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          Abstract

          Summary

          The ever-increasing growth of high-throughput sequencing technologies has led to a great acceleration of medical and biological research and discovery. As these platforms advance, the amount of information for diverse genomes increases at unprecedented rates. Confidentiality, integrity and authenticity of such genomic information should be ensured due to its extremely sensitive nature. In this paper, we propose Cryfa, a fast secure encryption tool for genomic data, namely in Fasta, Fastq, VCF, SAM and BAM formats, which is also capable of reducing the storage size of Fasta and Fastq files. Cryfa uses advanced encryption standard (AES) encryption combined with a shuffling mechanism, which leads to a substantial enhancement of the security against low data complexity attacks. Compared to AES Crypt, a general-purpose encryption tool, Cryfa is an industry-oriented tool, which is able to provide confidentiality, integrity and authenticity of data at four times more speed; in addition, it can reduce the file sizes to 1/3. Due to the absence of a method similar to Cryfa, we have simulated its behavior with a combination of encryption and compression tools, for comparison purpose. For instance, our tool is nine times faster than its fastest competitor in Fasta files. Also, Cryfa has a very low memory usage (only a few megabytes), which makes it feasible to run on any computer.

          Availability and implementation

          Source codes and binaries are available, under GPLv3, at https://github.com/pratas/cryfa.

          Supplementary information

          Supplementary data are available at Bioinformatics online.

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          Most cited references8

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          Scaling up: A guide to high-throughput genomic approaches for biodiversity analysis

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            Emerging viral diseases from a vaccinology perspective: preparing for the next pandemic

            Emerging infectious diseases will continue to threaten public health and are sustained by global commerce, travel and disruption of ecological systems. Most pandemic threats are caused by viruses from either zoonotic sources or vector-borne sources. Developing better ways to anticipate and manage the ongoing microbial challenge will be critical for achieving the United Nations Sustainable Development Goals and, conversely, each such goal will affect the ability to control infectious diseases. Here we discuss how technology can be applied effectively to better prepare for and respond to new viral diseases with a focus on new paradigms for vaccine development.
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              Extraterrestrial nucleobases in the Murchison meteorite

              Carbon-rich meteorites, carbonaceous chondrites, contain many biologically relevant organic molecules and delivered prebiotic material to the young Earth. We present compound-specific carbon isotope data indicating that measured purine and pyrimidine compounds are indigenous components of the Murchison meteorite. Carbon isotope ratios for uracil and xanthine of delta13C=+44.5per mil and +37.7per mil, respectively, indicate a non-terrestrial origin for these compounds. These new results demonstrate that organic compounds, which are components of the genetic code in modern biochemistry, were already present in the early solar system and may have played a key role in life's origin.
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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                Bioinformatics
                Bioinformatics
                bioinformatics
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                01 January 2019
                18 July 2018
                18 July 2018
                : 35
                : 1
                : 146-148
                Affiliations
                IEETA, Department of Electronics, Telecommunications and Informatics, University of Aveiro, Aveiro, Portugal
                Author notes
                To whom correspondence should be addressed. seyedmorteza@ 123456ua.pt
                Article
                bty645
                10.1093/bioinformatics/bty645
                6298042
                30020420
                d607b4ab-fbc2-4209-bc08-0096ceed1fc7
                © The Author(s) 2018. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 20 March 2018
                : 22 June 2018
                : 17 July 2018
                Page count
                Pages: 3
                Funding
                Funded by: European Fund for Regional Development
                Funded by: Operational Program Competitiveness Factors
                Funded by: Portuguese Foundation for Science and Technology
                Award ID: UID/CEC/00127/2013
                Award ID: PTCD/EEI-SII/6608/2014
                Award ID: PD/BD/113969/2015
                Categories
                Applications Notes
                Sequence Analysis

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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