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Self-assembly of Complex Two-dimensional Shapes from Single-stranded DNA Tiles
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Efficient algorithms for the computational design of optimal tiling arrays.

Alexander Schliep1, Roland Krause

  • 1Department Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 69-73, 14195 Berlin, Germany.

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|November 8, 2008
PubMed
Summary

Genome representation using oligonucleotide probes is crucial for analyzing gene expression and identifying novel genes. This study introduces a novel shortest path algorithm for optimal probe selection in tiling arrays, enhancing genomic analysis efficiency.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Genome representation by oligonucleotide probes is essential for various genomic analyses, including gene expression and novel gene detection.
  • Current tiling array designs face challenges in achieving high density, uniform melting temperatures, and minimizing cross-hybridization.
  • Efficient selection of probes is critical for accurate and comprehensive genomic studies.

Purpose of the Study:

  • To develop an optimized method for selecting oligonucleotide probes for genome representation in tiling arrays.
  • To formulate the probe selection as a minimal cost tiling path problem solvable via shortest path algorithms.
  • To incorporate experimental constraints and hybridization parameters into the probe selection process.

Main Methods:

  • Formulation of the minimal cost tiling path problem for oligonucleotide probe selection.
  • Application of multi-criterion optimization cast as a shortest path problem.
  • Utilizing standard linear-time algorithms for computing optimal tiling paths from large candidate sets.

Main Results:

  • Efficient computation of globally optimal tiling paths for millions of candidate oligonucleotides on standard hardware.
  • Spatially adaptive solutions tailored to specific problem instances and experimental constraints.
  • Integration of hybridization parameters, probe quality, and tiling density trade-offs.

Conclusions:

  • The developed shortest path approach provides an efficient and globally optimal solution for tiling array probe selection.
  • This method enhances the accuracy and comprehensiveness of genomic analyses, including small RNA detection.
  • A web application (http://tileomatic.org) is available to facilitate the practical application of this approach.