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Reconstructing the Evolutionary History of Complex Human Gene Clusters

  • Yu Zhang
  • Giltae Song
  • Tomáš Vinař
  • Eric D. Green
  • Adam Siepel
  • Webb Miller
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4955)

Abstract

Clusters of genes that evolved from single progenitors via repeated segmental duplications present significant challenges to the generation of a truly complete human genome sequence. Such clusters can confound both accurate sequence assembly and downstream computational analysis, yet they represent a hotbed of functional innovation, making them of extreme interest. We have developed an algorithm for reconstructing the evolutionary history of gene clusters using only human genomic sequence data. This method allows the tempo of large-scale evolutionary events in human gene clusters to be estimated, which in turn will facilitate primate comparative sequencing studies that will aim to reconstruct their evolutionary history more fully.

Keywords

Gene Cluster Duplication Event Tandem Duplication Target Distribution Atomic Boundary 
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

  • Yu Zhang
    • 1
    • 2
  • Giltae Song
    • 1
  • Tomáš Vinař
    • 3
  • Eric D. Green
    • 4
  • Adam Siepel
    • 3
  • Webb Miller
    • 1
  1. 1.Center for Comparative Genomics and Bioinformatics, 506B Wartik LabPenn State University, University ParkUSA
  2. 2.Department of StatisticsPenn State University, University ParkUSA
  3. 3.Department of Biological Statistics and Computational BiologyCornell UniversityIthacaUSA
  4. 4.Genome Technology Branch and NIH Intramural Sequencing CenterNational Human Genome Research Institute, National Institutes of HealthBethesdaUSA

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