Algorithms for Finding Gene Clusters
WABI '01 Proceedings of the First International Workshop on Algorithms in Bioinformatics
WABI '02 Proceedings of the Second International Workshop on Algorithms in Bioinformatics
The statistical significance of max-gap clusters
RCG'04 Proceedings of the 2004 RECOMB international conference on Comparative Genomics
Software note: Gene teams: a new formalization of gene clusters for comparative genomics
Computational Biology and Chemistry
Gene Team Tree: A Compact Representation of All Gene Teams
RECOMB-CG '08 Proceedings of the international workshop on Comparative Genomics
A Unified Approach for Reconstructing Ancient Gene Clusters
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Natural Parameter Values for Generalized Gene Adjacency
RECOMB-CG '09 Proceedings of the International Workshop on Comparative Genomics
Finding Nested Common Intervals Efficiently
RECOMB-CG '09 Proceedings of the International Workshop on Comparative Genomics
Computation of median gene clusters
RECOMB'08 Proceedings of the 12th annual international conference on Research in computational molecular biology
Consistency of sequence-based gene clusters
RECOMB-CG'10 Proceedings of the 2010 international conference on Comparative genomics
Individual gene cluster statistics in noisy maps
RCG'05 Proceedings of the 2005 international conference on Comparative Genomics
Integer linear programs for discovering approximate gene clusters
WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
Output-Sensitive Algorithms for Finding the Nested Common Intervals of Two General Sequences
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Inferring positional homologs with common intervals of sequences
RCG'06 Proceedings of the RECOMB 2006 international conference on Comparative Genomics
An algorithmic view on multi-related-segments: a unifying model for approximate common interval
TAMC'12 Proceedings of the 9th Annual international conference on Theory and Applications of Models of Computation
Hi-index | 0.01 |
There is widespread interest in comparative genomics in determining if historically and/or functionally related genes are spatially clustered in the genome, and whether the same sets of genes reappear in clusters in two or more genomes. We formalize and analyze the desirable properties of gene clusters and cluster definitions. Through detailed analysis of two commonly applied types of cluster, r-windows and max-gap, we investigate the extent to which a single definition can embody all of these properties simultaneously. We show that many of the most important properties are difficult to satisfy within the same definition. We also examine whether one commonly assumed property, which we call nestedness, is satisfied by the structures present in real genomic data.