Computational stochastics and bioinformatics

Computational stochastics
A coalescent hidden Markov model for ancestral analysis of the human, chimpanzee and gorilla genomes.

Principal investigators

Jens Ledet Jensen, Asger Hobolth

Research partners

Focus Points

Analysis of high-dimensional data, inference in evolutionary models

Recent Publications

  • A State Space Model Exhibiting a Cyclic Structure with an Application to Progesterone Concentration in Cow Milk
    Jørgen V. Hansen, Jens L. Jensen and Søren Højsgaard
  • Hobolth, A. (2008). A Markov Chain Monte Carlo Expectation Maximization
    algorithm for statistical analysis of DNA sequence evolution with
    neighbour-dependent substitution rates. Journal of Computational and Graphical
    Statistics, to appear.
  • Choi, S.C., Hobolth, A., Robinson, D.M., Kishino, H. and Thorne, J.L. (2007).
    Quantifying the Impact of Protein Tertiary Structure on Molecular Evolution.
    Molecular Biology and Evolution, 24, 1769-1782.
  • Hobolth, A., Christensen, O.F., Mailund, T. and Schierup, M.H. (2007). Genomic
    relationships and speciation times of human, chimpanzee, and gorilla inferred
    from a coalescent hidden Markov model. PLoS Genetics, 3, 294-304.
  • Hobolth, A., Nielsen, R., Wang, Y., Wu, F. and Tanksley, S.D. (2006).
    CpG+CpNpG analysis of protein coding sequences from tomato. Molecular Biology
    and Evolution, 23, 1318-1323.