Selected article for: "gene prediction and viral genome"

Author: Daley, Mark; McQuillan, Ian
Title: Viral Gene Compression: Complexity and Verification
  • Cord-id: xcii4zlt
  • Document date: 2005_1_1
  • ID: xcii4zlt
    Snippet: The smallest known biological organisms are, by far, the viruses. One of the unique adaptations that many viruses have aquired is the compression of the genes in their genomes. In this paper we study a formalized model of gene compression in viruses. Specifically, we define a set of constraints that describe viral gene compression strategies and investigate the properties of these constraints from the point of view of genomes as languages. We pay special attention to the finite case (representin
    Document: The smallest known biological organisms are, by far, the viruses. One of the unique adaptations that many viruses have aquired is the compression of the genes in their genomes. In this paper we study a formalized model of gene compression in viruses. Specifically, we define a set of constraints that describe viral gene compression strategies and investigate the properties of these constraints from the point of view of genomes as languages. We pay special attention to the finite case (representing real viral genomes) and describe a metric for measuring the level of compression in a real viral genome. An efficient algorithm for establishing this metric is given along with applications to real genomes including automated classification of viruses and prediction of horizontal gene transfer between host and virus.

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