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Bulletin of Mathematical Biology

, Volume 51, Issue 1, pp 39–54 | Cite as

Algorithms for the optimal identification of segment neighborhoods

  • Ivan E. Auger
  • Charles E. Lawrence
Article

Abstract

Two algorithms for the efficient identification of segment neighborhoods are presented. A segment neighborhood is a set of contiguous residues that share common features. Two procedures are developed to efficiently find estimates for the parameters of the model that describe these features and for the residues that define the boundaries of each segment neighborhood. The algorithms can accept nearly any model of segment neighborhood, and can be applied with a broad class of best fit functions including least squares and maximum likelihood. The algorithms successively identify the most important features of the sequence. The application of one of these methods to the haemagglutinin protein of influenza virus reveals a possible mechanism for conformational change through the finding of a break in a strong heptad repeat structure.

Keywords

Influenza Virus Heptad Coiled Coil Hydrophobic Segment Segmented Regression 
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

© Society for Mathematical Biology 1989

Authors and Affiliations

  • Ivan E. Auger
    • 1
  • Charles E. Lawrence
    • 1
  1. 1.Laboratory of BiometricsWadsworth Center for Laboratories and Research, New York State Department of HealthAlbanyU.S.A.

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