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The problem of clustering fingerprint vectors is an interesting problem inComputational Biology that has been proposed in (Figureroa et al. 2004). Inthis paper we show some improvements in closing the gaps between the knownlower bounds and upper bounds on the approximability of some variants of thebiological problem. Namely we are able to prove that the problem is APX-hardeven when each fingerprint contains only two unknown position. Moreover we havestudied some variants of the orginal problem, and we give two 2-approximationalgorithm for the IECMV and OECMV problems when the number of unknown entriesfor each vector is at most a constant.Comment: 13 pages, 4 figure

Fingerprint Clustering with Bounded Number of Missing Values