Approximation Algorithms Of Non-Unique Probes Selection For Biological Target Identification

Non-unique probes are used to identify the targets, i.e., viruses present in a given sample. Since the number of selected non-unique probes is equal to the number of hybridization experiments, it is important to find a minimum set of non-unique probes, which is NP-complete. Using d-disjunct matrix, we present two (1 + (d+ 1) logn)-approximation algorithms to identify at most d targets. Based on our selected non-unique probes, we also present the decoding algorithms with linear time complexity. In addition, our solutions are fault tolerant. The proposed algorithms can identify at most d targets in the presence of experimental errors.