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Buchkapitel

Efficient Computational Design of Tiling Arrays Using a Shortest Path Approach.

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons50523

Schliep,  Alexander
Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons50394

Krause,  Roland
Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Zitation

Schliep, A., & Krause, R. (2007). Efficient Computational Design of Tiling Arrays Using a Shortest Path Approach. In S. H. Raffaele Giancarlo (Ed.), Algorithms in Bioinformatics (pp. 383-394). Berlin / Heidelberg: Springer.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0010-82E1-1
Zusammenfassung
Genomic tiling arrays are a type of DNA microarrays which can investigate the complete genome of arbitrary species for which the sequence is known. The design or selection of suitable oligonucleotide probes for such arrays is however computationally difficult if features such as oligonucleotide quality and repetitive regions are to be considered. We formulate the minimal cost tiling path problem for the selection of oligonucleotides from a set of candidates, which is equivalent to a shortest path problem. An efficient implementation of Dijkstra’s shortest path algorithm allows us to compute globally optimal tiling paths from millions of candidate oligonucleotides on a standard desktop computer. The solution to this multi-criterion optimization is spatially adaptive to the problem instance. Our formulation incorporates experimental constraints with respect to specific regions of interest and tradeoffs between hybridization parameters, probe quality and tiling density easily. Solutions for the basic formulation can be obtained more efficiently from Monge theory.