Name
Abstract | ||
|---|---|---|
The problem of clustering fingerprint vectors is an interesting problem in Computational Biology that has been proposed in (6). 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. |
Year | Venue | Keywords |
|---|---|---|
2005 | CATS | data structure,upper bound,computational biology,lower bound,missing values |
DocType | Volume | Citations |
Conference | abs/cs/051 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paola Bonizzoni | 1 | 502 | 52.23 |
| Gianluca Della Vedova | 2 | 342 | 36.39 |
| Riccardo Dondi | 3 | 89 | 18.42 |