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Guided genome halving: provably optimal solutions provide good insights into the preduplication ancestral genome of Saccharomyces cerevisiae.

Haris Gavranović 1 Eric Tannier 2, 3
2 BEAGLE - Artificial Evolution and Computational Biology
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information, Inria Grenoble - Rhône-Alpes, LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558
Abstract : We present theoretical and practical advances on the Guided Genome Halving problem, a combinatorial optimisation problem which aims at proposing ancestral configurations of extant genomes when one of them has undergone a whole genome duplication. We provide a lower bound on the optimal solution, devise a heuristic algorithm based on subgraph identification, and apply it to yeast gene order data. On some instances, the computation of the bound yields a proof that the obtained solutions are optimal. We analyse a set of optimal solutions, compare them with a manually curated standard ancestor, showing that on yeast data, results coming from different methodologies are largely convergent: the optimal solutions are distant of at most one rearrangement from the reference.
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Haris Gavranović, Eric Tannier. Guided genome halving: provably optimal solutions provide good insights into the preduplication ancestral genome of Saccharomyces cerevisiae.. Pacific Symposium on Biocomputing, Jan 2010, Big Island, Hawaï, United States. pp.21-30, ⟨10.1142/9789814295291_0004⟩. ⟨hal-00681096⟩

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