On the tandem duplication-random loss model of genome rearrangement
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Finding All Sorting Tandem Duplication Random Loss Operations
CPM '09 Proceedings of the 20th Annual Symposium on Combinatorial Pattern Matching
Finding all sorting tandem duplication random loss operations
Journal of Discrete Algorithms
A framework for orthology assignment from gene rearrangement data
RCG'05 Proceedings of the 2005 international conference on Comparative Genomics
Quartet-based phylogeny reconstruction from gene orders
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
Linear programming for phylogenetic reconstruction based on gene rearrangements
CPM'05 Proceedings of the 16th annual conference on Combinatorial Pattern Matching
Using treemaps to visualize phylogenetic trees
ISBMDA'05 Proceedings of the 6th International conference on Biological and Medical Data Analysis
RAxML-OMP: an efficient program for phylogenetic inference on SMPs
PaCT'05 Proceedings of the 8th international conference on Parallel Computing Technologies
| Hi-index | 0.00 |
Phylogenetic reconstruction from gene-order datahas attracted attention from both biologists and computerscientists over the last few years. So far, our softwaresuite GRAPPA is the most accurate approach, but it requiresthat all genomes have identical gene content, witheach gene appearing exactly once in each genome. Someprogress has been made in handling genomes with unequalgene content, both in terms of computing pairwisegenomic distances and in terms of reconstruction.In this paper, we present a new approach for computingthe median of three arbitrary genomes and applyit to the reconstruction of phylogenies from arbitrarygene-order data. We implemented these methodswithin GRAPPAand tested them on simulated datasets undervarious conditions as well as on a real dataset ofchloroplast genomes; we report the results of our simulationsand our analysis of the real dataset and compare themto reconstructions made by using neighbor-joining and usingthe original GRAPPA on the same genomes withequalized gene contents. Our new approach is remarkablyaccurate both in simulations and on the real dataset,in contrast to the distance-based approaches and to reconstructionsusing the original GRAPPAapplied to equalizedgene contents.