Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Assignment of Orthologous Genes via Genome Rearrangement
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Power boosts for cluster tests
RCG'05 Proceedings of the 2005 international conference on Comparative Genomics
Conserved interval distance computation between non-trivial genomes
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
Exemplar Longest Common Subsequence
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
RECOMB-CG'07 Proceedings of the 2007 international conference on Comparative genomics
On the approximability of comparing genomes with duplicates
WALCOM'08 Proceedings of the 2nd international conference on Algorithms and computation
Inferring positional homologs with common intervals of sequences
RCG'06 Proceedings of the RECOMB 2006 international conference on Comparative Genomics
How pseudo-boolean programming can help genome rearrangement distance computation
RCG'06 Proceedings of the RECOMB 2006 international conference on Comparative Genomics
Non-breaking similarity of genomes with gene repetitions
CPM'07 Proceedings of the 18th annual conference on Combinatorial Pattern Matching
| Hi-index | 0.00 |
In this paper, we are interested in the algorithmic complexity of computing (dis)similarity measures between two genomes when they contain duplicated genes. In that case, there are usually two main ways to compute a given (dis)similarity measure M between two genomes G1 and G2: the first model, that we will call the matching model, consists in computing a one-to-one correspondence between genes of G1 and genes of G2, in such a way that M is optimized in the resulting permutation. The second model, called the exemplar model, consists in keeping in G1 (resp. G2) exactly one copy of each gene, thus deleting all the other copies, in such a way that M is optimized in the resulting permutation. We present here different results concerning the algorithmic complexity of computing three different similarity measures (number of common intervals, MAD number and SAD number) in those two models, basically showing that the problem becomes NP-completeness for each of them as soon as genomes contain duplicates. In the case of MAD and SAD, we actually prove that, under both models, both MAD and SAD problems are APX-hard.