Showing papers by "Olivier Elemento published in 2003"

IMGT/PhyloGene: an on-line tool for comparative analysis of immunoglobulin and T cell receptor genes.

Abstract: IMGT/PhyloGene is an on-line software package for comparative analysis of immunoglobulin (IG) and T cell receptor (TR) variable genes of all vertebrate species, newly implemented in IMGT, the international ImMunoGeneTics information system ® . IMGT/PhyloGene is strongly associated with the IMGT gene and allele nomenclature and with the IMGT unique numbering for V-REGION, which directly creates standardized alignments from IMGT reference sequences. IMGT/PhyloGene is the first tool to use the IMGT expertized and standardized data for automated comparative analyses, and the first on-line software package for phylogenetic reconstruction to be integrated to a sequence database. Starting from a standardized alignment of selected sequences, IMGT/PhyloGene computes a matrix of evolutionary distances, builds a tree using the Neighbor-Joining (NJ) algorithm, and outputs various graphical tree representations. The resulting IMGT/PhyloGene tree is then used as a support for studying the evolution of particular subregions, such as the CDR-IMGT (Complementarity Determining Regions) or the V-RS (Variable gene Recombination Signals). IMGT/PhyloGene is freely available at http://imgt.cines.fr .

An exact and polynomial distance-based algorithm to reconstruct single copy tandem duplication trees

Abstract: The problem of reconstructing the duplication tree of a set of tandemly repeated sequences which are supposed to have arisen by unequal recombination, was first introduced by Fitch (1977), and has recently received a lot of attention. In this paper, we deal with the restricted problem of reconstructing single copy duplication trees. We describe an exact and polynomial distance based algorithm for solving this problem, the parsimony version of which has previously been shown to be NP-hard (like most evolutionary tree reconstruction problems). This algorithm is based on the minimum evolution principle, and thus involves selecting the shortest tree as being the correct duplication tree. After presenting the underlying mathematical concepts behind the minimum evolution principle, and some of its benefits (such as consistency), we provide a new recurrence equation to estimate the tree length using ordinary least-squares, given a matrix of pairwise distances between the copies. We then show how this equation naturally forms the dynamic programming framework on which our algorithm is based, and provide an implementation in O(n3) time and O(n2) space, where n is the number of copies.