In Silico Expression Profiles of Human Endogenous Retroviruses

  • Merja Oja
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4774)

Abstract

Human endogenous retroviruses (HERVs) are remnants of ancient retrovirus infections and now reside within the human DNA. Recently HERV expression has been detected in both normal and diseased tissues. However, the patterns of expression of individual HERV sequences are mostly unknown. In this work we use a generative mixture model, based on hidden Markov models, for estimating the activities of individual HERV sequences from databases of expressed sequences. We determine the relative activities of sixty HERVs from the HML2 group in five human tissues, i.e. we estimate the expression profile of each HERV. This allows us to gain insight into HERV function.

Keywords

Hide Markov Model UCSC Genome Browser Hide Markov Model Model Long Terminal Repeat Sequence Generative Mixture Model 
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 2007

Authors and Affiliations

  • Merja Oja
    • 1
  1. 1.Helsinki Institute for Information Technology, Helsinki University of Technology, P.O. Box 5400, 02015 TKK, Finland, and Department of Computer Science, University of Helsinki 

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