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Related Concept Videos

Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Evolutionary Relationships through Genome Comparisons02:54

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Private and Efficient Query Processing on Outsourced Genomic Databases.

Reza Ghasemi, Md Momin Al Aziz, Noman Mohammed

    IEEE Journal of Biomedical and Health Informatics
    |November 12, 2016
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    Summary
    This summary is machine-generated.

    This study introduces a privacy-preserving model for cloud-based genomic data outsourcing. It enables secure query processing, protecting sensitive genomic information from potential breaches.

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    Area of Science:

    • Genomics and Bioinformatics
    • Cloud Computing Security
    • Data Privacy

    Background:

    • Genomic data applications are expanding across healthcare, research, and forensics.
    • Challenges include high costs, computational demands, and data accessibility issues.
    • Cloud computing offers solutions but raises concerns about data breaches and untrusted providers.

    Purpose of the Study:

    • To propose a privacy-preserving model for outsourcing genomic databases to the cloud.
    • To enable secure and efficient query processing on outsourced genomic data.
    • To address data owner reluctance due to privacy concerns.

    Main Methods:

    • Developed a privacy-preserving model for cloud-based genomic data outsourcing.
    • Implemented data perturbation techniques including record permutation and addition of fake records.
    • Enabled secure evaluation of count and top-k queries.

    Main Results:

    • The proposed model ensures privacy protection for genomic databases.
    • Secure and efficient query processing is achieved on outsourced data.
    • Experimental results show query times of approximately 100s for count and 150s for top-k queries on large datasets.

    Conclusions:

    • The developed model effectively balances the utility of cloud-based genomic data with robust privacy guarantees.
    • It facilitates secure sharing and analysis of sensitive genomic information.
    • This approach can encourage wider adoption of cloud computing for genomic applications.