Group Testing With DNA Chips: Generating Designs and Decoding Experiments
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Integer linear programming approaches for non-unique probe selection
Discrete Applied Mathematics
Pattern Recognition Letters
Space pruning monotonic search for the non-unique probe selection problem
International Journal of Bioinformatics Research and Applications
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In order to accurately measure the gene expression levels in microarray experiments, it is crucial to design unique, highly specific and highly sensitive oligonucleotide probes for the identification of biological agents such as genes in a sample. Unique probes are difficult to obtain for closely related genes such as the known strains of HIV genes. The non-uniqueprobe selection problem is to find one of the smallest probe set that is able to uniquely identify targets in a biological sample. This is an NP-hard problem. We present heuristic for finding near-minimal non-unique probe sets. Our method is a variant of the sequential forward selectionalgorithm, which used for feature subset selection in pattern recognition systems. The heuristic is guided by a probe set selection criterion which evaluates the efficiency and the effectiveness of a probe set in classifying targets genes as present or absent in a biological sample. Our methods outperformed all currently published greedy algorithms for this problem.