Software note: Gene teams: a new formalization of gene clusters for comparative genomics

Authors:
Nicolas Luc;Jean-Loup Risler;Anne Bergeron;Mathieu Raffinot
Affiliations:
CNRS - Laboratoire Génome et Informatique, Tour Evry 2, 523, Place des Terrasses de 1'Agora, 91034 Evry, France;CNRS - Laboratoire Génome et Informatique, Tour Evry 2, 523, Place des Terrasses de 1'Agora, 91034 Evry, France;LaCIM, Université du Québec í Montréal, Montréal, Québec, Canada;CNRS - Laboratoire Génome et Informatique, Tour Evry 2, 523, Place des Terrasses de 1'Agora, 91034 Evry, France
Venue:
Computational Biology and Chemistry
Year:
2003

Citing 3
Cited 9

Algorithms for Finding Gene Clusters

WABI '01 Proceedings of the First International Workshop on Algorithms in Bioinformatics
The Algorithmic of Gene Teams

WABI '02 Proceedings of the Second International Workshop on Algorithms in Bioinformatics
Finding All Common Intervals of k Permutations

CPM '01 Proceedings of the 12th Annual Symposium on Combinatorial Pattern Matching

Identifying conserved gene clusters in the presence of orthologous groups

RECOMB '04 Proceedings of the eighth annual international conference on Resaerch in computational molecular biology
An algorithmic view of gene teams

Theoretical Computer Science
OrthoCluster: a new tool for mining synteny blocks and applications in comparative genomics

EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Improved Algorithms for the Gene Team Problem

COCOA '09 Proceedings of the 3rd International Conference on Combinatorial Optimization and Applications
The incompatible desiderata of gene cluster properties

RCG'05 Proceedings of the 2005 international conference on Comparative Genomics
A parallel algorithm for solving the reversal median problem

PPAM'05 Proceedings of the 6th international conference on Parallel Processing and Applied Mathematics
A New Efficient Algorithm for the Gene-Team Problem on General Sequences

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Output-Sensitive Algorithms for Finding the Nested Common Intervals of Two General Sequences

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
The statistical significance of max-gap clusters

RCG'04 Proceedings of the 2004 RECOMB international conference on Comparative Genomics

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Abstract

This paper describes an efficient algorithm based on a new concept called gene team for detecting conserved gene clusters among an arbitrary number of chromosomes. Within the clusters, neither the order of the genes nor their orientation need be conserved. In addition, insertion of foreign genes within the clusters are permitted to a user-defined extent. This algorithm has been implemented in a publicly available team software that proves to be an efficient tool for systematic searches of conserved gene clusters. Examples of actual biological results are provided. The software is downloadable from http://www-igm.univ-mlv.fr/~raffinot/geneteam.html.