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HCV Quasispecies Assembly Using Network Flows

  • Kelly Westbrooks
  • Irina Astrovskaya
  • David Campo
  • Yury Khudyakov
  • Piotr Berman
  • Alex Zelikovsky
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4983)

Abstract

Understanding how the genomes of viruses mutate and evolve within infected individuals is critically important in epidemiology. By exploiting knowledge of the forces that guide viral microevolution, researchers can design drugs and treatments that are effective against newly evolved strains. Therefore, it is critical to develop a method for typing the genomes of all of the variants of a virus (quasispecies) inside an infected individual cell.

In this paper, we focus on sequence assembly of Hepatitis C Virus (HCV) based on 454 Lifesciences system that produces around 250K reads each 100-400 base long. We introduce several formulations of the quasispecies assembly problem and a measure of the assembly quality. We also propose a novel scalable assembling method for quasispecies based on a novel network flow formulation. Finally, we report the results of assembling 44 quasispecies from the 1700 bp long E1E2 region of HCV.

Keywords

Problem Instance Directed Acyclic Graph Network Flow Switching Error Consensus Genome 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Kelly Westbrooks
    • 1
  • Irina Astrovskaya
    • 1
  • David Campo
    • 2
  • Yury Khudyakov
    • 2
  • Piotr Berman
    • 3
  • Alex Zelikovsky
    • 1
  1. 1.Department of Computer ScienceGeorgia State UniversityAtlanta 
  2. 2.Centers for Disease Control and PreventionAtlanta 
  3. 3.Department of Computer Science and EngineeringPennsylvania State UniversityUniversity Park 

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