A clustering algorithm for interval graph test on noisy data

Authors:
Wei-Fu Lu;Wen-Lian Hsu
Affiliations:
Institute of Computer and Information Science, National Chiao Tung University, Hsin-Chu, Taiwan, ROC;Institute of Information Science, Academia Sinica, Taipei, Taiwan, ROC
Venue:
WEA'03 Proceedings of the 2nd international conference on Experimental and efficient algorithms
Year:
2003

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Abstract

An interval graph is the intersection graph of a collection of intervals. One important application of interval graph is physical mapping in genome research, that is, to reassemble the clones to determine the relative position of fragments of DNAalon g the genome. The linear time algorithm by Booth and Lueker (1976) for this problem has a serious drawback: the data must be error-free. However, laboratory work is never flawless. We devised a new iterative clustering algorithm for this problem, which can accommodate noisy data and produce a likely interval model realizing the original graph.