Computer Science and Engineering
 Gothenburg University | Chalmers

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Tiling: Design of Tiling Arrays

The representation of a genome by oligonucleotide probes is a prerequisite for the analysis of many of its basic properties, such as transcription factor binding sites, chromosomal breakpoints, gene expression of known genes and detection of novel genes, in particular those coding for small RNAs. An ideal representation would consist of a high density set of oligonucleotides with similar melting temperatures that do not cross-hybridize with other regions of the genome and are equidistantly spaced. The implementation of such design is typically called a tiling array or genome array.

We formulate the minimal cost tiling path problem for the selection of oligonucleotides from a set of candidates. Computing the selection of probes requires multi-criterion optimization, which we cast into a shortest path problem. Standard algorithms running in linear time allow us to compute globally optimal tiling paths from millions of candidate oligonucleotides on a standard desktop computer for most problem variants. The solutions to this multi-criterion optimization are 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.


Hafemeister, Christoph and Krause, Roland and Schliep, Alexander. Selecting oligonucleotide probes for whole-genome tiling arrays with a cross-hybridization potential (2011) [details]

Hafemeister, Christoph. Efficient Computation of Probe Qualities (2008) [details]

Macula, A.J. and Schliep, A. and Bishop, M.A. and Renz, T.E.. New, improved, and practical k-stem sequence similarity measures for probe design (2008) [details]

Schliep, Alexander and Krause,Roland. Efficient algorithms for the computational design of optimal tiling arrays (2008) [details]

Schliep, Alexander and Krause, Roland. Efficient Computational Design of Tiling Arrays Using a Shortest Path Approach (2007) [details]

Contact: Alexander Schliep (