缺失指纹向量的近似聚类
Approximating Clustering of Fingerprint Vectors with Missing Values
摘要：
聚类指纹向量的问题是计算生物学中的一个有趣的问题，已经在（Figureroa et al.2004）中提出。在本文中，我们展示了一些改进，在关闭已知的下限和上限之间的差距的生物问题的一些变种的近似性。也就是说，我们能够证明，即使每个指纹只包含两个未知位置的问题是APX困难的。此外，我们还研究了原问题的一些变形，当每个向量的未知元素个数至多为常数时，给出了IECMV和OECMV问题的两个2-近似算法。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
