  The problem of clustering fingerprint vectors is an interesting problem in
Computational Biology that has been proposed in (Figureroa et al. 2004). In
this paper we show some improvements in closing the gaps between the known
lower bounds and upper bounds on the approximability of some variants of the
biological problem. Namely we are able to prove that the problem is APX-hard
even when each fingerprint contains only two unknown position. Moreover we have
studied some variants of the orginal problem, and we give two 2-approximation
algorithm for the IECMV and OECMV problems when the number of unknown entries
for each vector is at most a constant.
