Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-540-87989-3_8
DC FieldValue
dc.titleGene team tree: A compact representation of all gene teams
dc.contributor.authorZhang, M.
dc.contributor.authorLeong, H.W.
dc.date.accessioned2013-07-04T08:22:25Z
dc.date.available2013-07-04T08:22:25Z
dc.date.issued2008
dc.identifier.citationZhang, M.,Leong, H.W. (2008). Gene team tree: A compact representation of all gene teams. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5267 LNBI : 100-112. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-540-87989-3_8" target="_blank">https://doi.org/10.1007/978-3-540-87989-3_8</a>
dc.identifier.isbn3540879889
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41221
dc.description.abstractThe identification of conserved gene clusters is an important step towards understanding genome evolution and predicting the function of genes. Gene team is a model for conserved gene clusters that takes into account the position of genes on a genome. Existing algorithms for finding gene teams require the user to specify the maximum distance between adjacent genes in a team. However, determining suitable values for this parameter, δ, is non-trivial. Instead of trying to determine a single best value, we propose constructing the gene team tree (GTT), which is a compact representation of all gene teams for every possible value of δ. Our algorithm for computing the GTT extends existing gene team mining algorithms without increasing their time complexity. We compute the GTT for E. coli K-12 and B. subtilis and show that E. coli K-12 operons are recovered at different values of δ. We also describe how to compute the GTT for multi-chromosomal genomes and illustrate using the GTT for the human and mouse genomes. © 2008 Springer-Verlag.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-540-87989-3_8
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1007/978-3-540-87989-3_8
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume5267 LNBI
dc.description.page100-112
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.