On the Complexity of Sparse Exon Assembly

  • Carmel Kent
  • Gad M. Landau
  • Michal Ziv-Ukelson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3537)


Gene structure prediction is one of the most important problems in computational molecular biology. A combinatorial approach to the problem, denoted Gene Prediction via Spliced Alignment, was introduced by Gelfand, Mironov and Pevzner [5]. The method works by finding a set of blocks in a source genomic sequence S whose concatenation (splicing) fits a target gene T belonging to a homologous species. Let S,T and the candidate exons be sequences of size O(n). The innovative algorithm described in [5] yields an O(n 3) result for spliced alignment, regardless of filtration mode.

In this paper we suggest a new algorithm which targets the case where filtering has been applied to the data, resulting in a set of O(n) candidate exon blocks. Our algorithm yields an \(O(n^2 \sqrt{n})\) solution for this case.


Edit Distance Steiner Point Grid Graph Linear Encode Space Complexity Analysis 
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

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Carmel Kent
    • 1
  • Gad M. Landau
    • 1
    • 2
  • Michal Ziv-Ukelson
    • 3
  1. 1.Dept. of Computer ScienceHaifa UniversityHaifaIsrael
  2. 2.Department of Computer and Information SciencePolytechnic UniversityBrooklynUSA
  3. 3.Dept. of Computer ScienceTechnion – Israel Institute of TechnologyHaifaIsrael

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