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The Sequence Reconstruction Problem

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Discrete and Topological Models in Molecular Biology

Part of the book series: Natural Computing Series ((NCS))

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Abstract

Despite recent advances, assembly of genomes from the high-throughput data generated by the next-generation sequencing (NGS) technologies remains one of the most challenging tasks in modern biology. Here we address the sequence reconstruction problem, whereby, for a given collection of subsequences or factors, one has to determine the set of sequences compliant with the collection. First, we give a brief review of sequencing technologies, along with an exposition of the advantages and shortcomings of the existing algorithmic approaches to sequence assembly. In addition, we enumerate some properties of subsequences, which have been overlooked in the existing heuristic solutions despite their effect on the quality of the assembly. We then give an overview of the sequence reconstruction problem from a language-theoretic perspective, and present a comprehensive review of theoretical results that may prove relevant to the genome assembly problem. Finally, we outline a new optimization-based formulation which casts the sequence reconstruction problem as a quadratic integer programming problem.

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Author information

Authors and Affiliations

  1. The University of Tampa, Tampa, FL, USA

    Angela Angeleska

  2. Systems Biology and Mathematical Modeling Group, Max Planck Institute for Molecular Plant Physiology – Golm, Potsdam, Germany

    Sabrina Kleessen & Zoran Nikoloski

Authors
  1. Angela Angeleska
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  2. Sabrina Kleessen
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  3. Zoran Nikoloski
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Correspondence to Angela Angeleska .

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Editors and Affiliations

  1. Dept. Mathematics & Statistics, University of South Florida, Tampa, Florida, USA

    Nataša Jonoska

  2. Dept. Mathematics & Statistics, University of South Florida, Tampa, Florida, USA

    Masahico Saito

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Angeleska, A., Kleessen, S., Nikoloski, Z. (2014). The Sequence Reconstruction Problem. In: Jonoska, N., Saito, M. (eds) Discrete and Topological Models in Molecular Biology. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40193-0_2

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  • DOI: https://doi.org/10.1007/978-3-642-40193-0_2

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