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Algorithms with Restrictive Input Constrains on Genome Exemplar Distance Caculation

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Business, Economics, Financial Sciences, and Management

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 143))

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Abstract

The comparative study of gene order rearrangements has been restricted to the case when the genes in one genome are homologous to at most one gene in the other genome. Sankoff (1999) proposes the estimation of true exemplars, a selection of one gene from each gene family in both genomes such that the distance between the resulting exemplar strings is minimized, which is called exemplar distance. David Bryant in his paper show that the calculation of the exemplar distance between two genomes is NP-hard for both the signed reversals distance and the breakpoint distance, even with quite restrictive conditions on the input. Limite the input according to strictive conditions used by David Bryants’ proof, here we provides two algorithm to solve problem under some input conditions. one is branch and bound algorithms ,the other is Greedy Algorithm for both distances .different DATA can use different Algorithm to get better performance.

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References

  1. Sankoffd: Genome rearrangements with gene of families. J. Bioinformatics. 15, 909–917 (1999)

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  2. Sankoff, D., Nadeau, J.H. (eds.): Comparative Genomics. Kluwer Academic Publishers, Netherlands (2000)

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  3. Zhu, D., Ma, S.: Algorithm design and analysis. Higher Education Press, China (2009)

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Correspondence to Yehong Chen .

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© 2012 Springer-Verlag GmbH Berlin Heidelberg

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Chen, Y., Zhu, D., Tang, W., Chen, Q., Zhang, J. (2012). Algorithms with Restrictive Input Constrains on Genome Exemplar Distance Caculation. In: Zhu, M. (eds) Business, Economics, Financial Sciences, and Management. Advances in Intelligent and Soft Computing, vol 143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27966-9_83

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  • DOI: https://doi.org/10.1007/978-3-642-27966-9_83

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27965-2

  • Online ISBN: 978-3-642-27966-9

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