Geometric applications of a matrix searching algorithm
SCG '86 Proceedings of the second annual symposium on Computational geometry
Fibonacci heaps and their uses in improved network optimization algorithms
Journal of the ACM (JACM)
The concave least-weight subsequence problem revisited
Journal of Algorithms
A linear-time algorithm for concave one-dimensional dynamic programming
Information Processing Letters
Sequence comparison with mixed convex and concave costs
Journal of Algorithms
Dynamic programming with convexity, concavity and sparsity
Theoretical Computer Science - Selected papers of the Combinatorial Pattern Matching School
Finding a minimum weight K-link path in graphs with Monge property and applications
SCG '93 Proceedings of the ninth annual symposium on Computational geometry
Perspectives of Monge properties in optimization
Discrete Applied Mathematics
Introduction to Algorithms
Group Testing With DNA Chips: Generating Designs and Decoding Experiments
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Replacing suffix trees with enhanced suffix arrays
Journal of Discrete Algorithms - SPIRE 2002
Efficient computational design of tiling arrays using a shortest path approach
WABI'07 Proceedings of the 7th international conference on Algorithms in Bioinformatics
Selecting Oligonucleotide Probes for Whole-Genome Tiling Arrays with a Cross-Hybridization Potential
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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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 trade offs between hybridization parameters, probe quality and tiling density easily.