Three partition refinement algorithms
SIAM Journal on Computing
Introduction to algorithms
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
Software note: Gene teams: a new formalization of gene clusters for comparative genomics
Computational Biology and Chemistry
Fast algorithms for identifying maximal common connected sets of interval graphs
Discrete Applied Mathematics
Improved approximate common interval
Information Processing Letters
Evolution under Reversals: Parsimony and Conservation of Common Intervals
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Theoretical Computer Science
Gene Team Tree: A Compact Representation of All Gene Teams
RECOMB-CG '08 Proceedings of the international workshop on Comparative Genomics
Discovering cis-regulatory modules by optimizing barbecues
Discrete Applied Mathematics
Improved Algorithms for the Gene Team Problem
COCOA '09 Proceedings of the 3rd International Conference on Combinatorial Optimization and Applications
Algorithms for computing bidirectional best hit r-window gene clusters
FAW-AAIM'11 Proceedings of the 5th joint international frontiers in algorithmics, and 7th international conference on Algorithmic aspects in information and management
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
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)
Revisiting t. uno and m. yagiura's algorithm
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
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Comparative genomics is a growing field in computational biology, and one of its typical problem is the identification of sets of orthologous genes that have virtually the same function in several genomes. Many different bioinformatics approaches have been proposed to define these groups, often based on the detection of sets of genes that are "not too far" in all genomes. In this paper, we propose a unifying concept, called gene teams, which can be adapted to various notions of distance. We present two algorithms for identifying gene teams formed by n genes placed on m linear chromosomes. The first one runs in O(mn log2n) and uses a divide and conquer approach based on the formal properties of gene teams. We next propose an optimization of the original algorithm, and, in order to better understand the complexity bound of the algorithms, we recast the problem in the Hopcroft's partition refinement framework. This allows us to analyze the complexity of the algorithms with elegant amortized techniques. Both algorithms require linear space. We also discuss extensions to circular chromosomes that achieve the same complexity.