Thomas Wim Hamelryck

Thomas Wim Hamelryck

Professor

ORCID: 0000-0003-2917-3602

Publication year:
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1 - 5 out of 5Page size: 10
  1. 2009
  2. Published

    A probabilistic approach to protein structure prediction: PHAISTOS in CASP8

    Borg, M., Boomsma, Wouter, Ferkinghoff-Borg, J., Frellsen, J., Harder, T. P., Mardia, K., Røgen, P., Stovgaard, K. & Hamelryck, Thomas Wim, 2009, LASR 2009 — Statistical Tools for Challenges in Bioinformatics. Proceedings. Gusnanto, A., Mardia, K. V. & Fallaize, C. J. (eds.). University of Leeds, p. 65-70 6 p.

    Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

  3. Published

    A probabilistic approach to protein structureprediction: PHAISTOS in CASP8

    Borg, M., Boomsma, Wouter, Ferkinghoff-Borg, J., Frellsen, J., Harder, T. P., Mardia, K. V., Røgen, P., Stovgaard, K. & Hamelryck, Thomas Wim, 2009, In: School of Mathematics. p. 65-70

    Research output: Contribution to journal › Journal article › Research › peer-review

  4. Published

    A probabilistic model of RNA conformational space

    Frellsen, J., Moltke, Ida, Thiim, M., Mardia, K. V., Ferkinghoff-Borg, J. & Hamelryck, Thomas Wim, 2009, In: PLoS Computational Biology. 5, 6, p. e1000406

    Research output: Contribution to journal › Journal article › Research › peer-review

  5. Published

    Biopython: freely available Python tools for computational molecular biology and bioinformatics

    Cock, P. J. A., Antao, T., Chang, J. T., Chapman, B. A., Cox, C. J., Dalke, A., Friedberg, I., Hamelryck, Thomas Wim, Kauff, F., Wilczynski, B. & de Hoon, M. J. L., 2009, In: Bioinformatics. 25, 11, p. 1422-3 1 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  6. Published

    Probabilistic models and machine learning in structural bioinformatics

    Hamelryck, Thomas Wim, 2009, In: Statistical Methods in Medical Research. 18, 5, p. 505-26 21 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

ID: 5765