J Gorodkin

Summary

Affiliation: Center for Biological Sequence Analysis
Country: Denmark

Publications

  1. ncbi request reprint Finding common sequence and structure motifs in a set of RNA sequences
    J Gorodkin
    Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
    Proc Int Conf Intell Syst Mol Biol 5:120-3. 1997
  2. ncbi request reprint Displaying the information contents of structural RNA alignments: the structure logos
    J Gorodkin
    Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
    Comput Appl Biosci 13:583-6. 1997
  3. ncbi request reprint Universal distribution of saliencies for pruning in layered neural networks
    J Gorodkin
    CONNECT, The Niels Bohr Institute, Copenhagen, Denmark
    Int J Neural Syst 8:489-98. 1997

Collaborators

Detail Information

Publications3

  1. ncbi request reprint Finding common sequence and structure motifs in a set of RNA sequences
    J Gorodkin
    Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
    Proc Int Conf Intell Syst Mol Biol 5:120-3. 1997
    ..Example solutions, and comparisons with other approaches, are provided. The solutions include finding consensus structures identical to published ones...
  2. ncbi request reprint Displaying the information contents of structural RNA alignments: the structure logos
    J Gorodkin
    Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark
    Comput Appl Biosci 13:583-6. 1997
    ..18, 6097-6100, 1990) to incorporate prior frequencies on the bases, allow for gaps in the alignments, and indicate the mutual information of base-paired regions in RNA...
  3. ncbi request reprint Universal distribution of saliencies for pruning in layered neural networks
    J Gorodkin
    CONNECT, The Niels Bohr Institute, Copenhagen, Denmark
    Int J Neural Syst 8:489-98. 1997
    ..Our results reveal unexpected universal properties of the log-saliency distribution and suggest a novel algorithm for saliency-based weight ranking that avoids the numerical cost of second derivative evaluations...