unique-probe-sol - BIOINFORMATICS Vol 20 Suppl 1 2004 pages...

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BIOINFORMATICS Vol. 20 Suppl. 1 2004, pages i186–i193 DOI: 10.1093/bioinformatics/bth936 Optimal robust non-unique probe selection using Integer Linear Programming Gunnar W. Klau 1 , Sven Rahmann 2,3, , Alexander Schliep 2 , Martin Vingron 2 and Knut Reinert 3, 1 Institute of Computer Graphics and Algorithms, Vienna University of Technology, Favoritenstraße 9-11, 1040 Vienna, Austria, 2 Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestraße 73, D-14195 Berlin, Germany and 3 Algorithmic Bioinformatics, Free University Berlin, Takustraße 9, 14195 Berlin, Germany Received on January 15, 2004; accepted on March 1, 2004 ABSTRACT Motivation: Besides their prevalent use for analyzing gene expression, microarrays are an efficient tool for biological, medical and industrial applications due to their ability to assess the presence or absence of biological agents, the targets, in a sample. Given a collection of genetic sequences of targets one faces the challenge of finding short oligonucleotides, the probes, which allow detection of targets in a sample. Each hybridization experiment determines whether the probe binds to its corresponding sequence in the target. Depending on the problem, the experiments are conducted using either unique or non-unique probes and usually assume that only one target is present in the sample. The problem at hand is to compute a design, i.e. a minimal set of probes that allows to infer the targets in the sample from the result of the hybridization experi- ment. If we allow to test for more than one target in the sample, the design of the probe set becomes difficult in the case of non-unique probes. Results: Building upon previous work on group testing for microarrays, we describe the first approach to select a minimal probe set for the case of non-unique probes in the presence of a small number of multiple targets in the sample.The approach is based on an ILP formulation and a branch-and-cut algorithm. Our preliminary implementation greatly reduces the number of probes needed while preserving the decoding capabilities. Availability: http://www.inf.fu-berlin.de/inst/ag-bio Contact: [email protected] 1 INTRODUCTION Microarrays are a widely used tool as they provide a cost- efficient way to determine levels of specified RNA or DNA molecules in a biological sample. Typically, one measures the amount of gene expression in a cell by observing hybridization To whom correspondence should be addressed. Present address: Genome Informatics, Faculty of Technology, University of Bielefeld, D-33595 Bielefeld, Germany. Table 1. Target-probe incidence matrix H p 1 p 2 p 3 p 4 p 5 p 6 p 7 p 8 p 9 t 1 111011000 t 2 101100110 t 3 011101101 t 4 010010111 of mRNA to different probes on a microarray, each probe targeting a specific gene. A different and likewise important application, arising for example in medicine, environmental sciences, industrial quality control or biothreat reduction, is the identification of biological agents in a sample.
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unique-probe-sol - BIOINFORMATICS Vol 20 Suppl 1 2004 pages...

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