Estimation of human endogeneous retrovirus activities from expressed sequence databases

Reference:

Merja Oja, Jaakko Peltonen, and Samuel Kaski. Estimation of human endogeneous retrovirus activities from expressed sequence databases. In Juho Rousu, Samuel Kaski, and Esko Ukkonen, editors, Probabilistic Modeling and Machine Learning in Structural and Systems Biology. Workshop Proceedings; Tuusula, Finland, June 17-18, pages 50–54, Helsinki, Finland, 2006. University of Helsinki.

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 tissues and diseased patients. However, the activities (expression levels) of individual HERV sequences are mostly unknown. In this work we introduce a generative mixture model, based on Hidden Markov Models, for estimating the activities of the individual HERV sequences from databases of expressed sequences. We determine the relative activities of 91 HERVs; the majority of their activities were previously unknown. We also empirically justify a faster heuristic method for HERV activity estimation.

Suggested BibTeX entry:

@inproceedings{Oja06pmsb,
    address = {Helsinki, Finland},
    author = {Merja Oja and Jaakko Peltonen and Samuel Kaski},
    booktitle = {Probabilistic Modeling and Machine Learning in Structural and Systems Biology. Workshop Proceedings; Tuusula, Finland, June 17-18},
    editor = {Juho Rousu and Samuel Kaski and Esko Ukkonen},
    pages = {50-54},
    publisher = {University of Helsinki},
    title = {Estimation of human endogeneous retrovirus activities from expressed sequence databases},
    year = {2006},
}