TY - GEN
T1 - Gene teams with relaxed proximity constraint
AU - Kim, Sun
AU - Choi, Jeong Hyeon
AU - Yang, Jiong
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2005
Y1 - 2005
N2 - Functionally related genes co-evolve, probably due to the strong selection pressure in evolution. Thus we expect that they are present in multiple genomes. Physical proximity among genes, known as gene team, is a very useful concept to discover functionally related genes in multiple genomes. However, there are also many gene sets that do not preserve physical proximity. In this paper, we generalized the gene team model, that looks for gene clusters in a physically clustered form, to multiple genome cases with relaxed constraint. We propose a novel hybrid pattern model that combines the set and the sequential pattern models. Our model searches for gene clusters with and/or without physical proximity constraint. This model is implemented and tested with 97 genomes (120 replicons). The result was analyzed to show the usefulness of our model. Especially, analysis of gene clusters that belong to B. subtilis and E. coli demonstrated that our model predicted many experimentally verified operons and functionally related clusters. Our program is fast enough to provide a sevice on the web at http://platcom.informatics.indiana.edu/platcom/. Users can select any combination of 97 genomes to predict gene teams.
AB - Functionally related genes co-evolve, probably due to the strong selection pressure in evolution. Thus we expect that they are present in multiple genomes. Physical proximity among genes, known as gene team, is a very useful concept to discover functionally related genes in multiple genomes. However, there are also many gene sets that do not preserve physical proximity. In this paper, we generalized the gene team model, that looks for gene clusters in a physically clustered form, to multiple genome cases with relaxed constraint. We propose a novel hybrid pattern model that combines the set and the sequential pattern models. Our model searches for gene clusters with and/or without physical proximity constraint. This model is implemented and tested with 97 genomes (120 replicons). The result was analyzed to show the usefulness of our model. Especially, analysis of gene clusters that belong to B. subtilis and E. coli demonstrated that our model predicted many experimentally verified operons and functionally related clusters. Our program is fast enough to provide a sevice on the web at http://platcom.informatics.indiana.edu/platcom/. Users can select any combination of 97 genomes to predict gene teams.
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U2 - 10.1109/csb.2005.33
DO - 10.1109/csb.2005.33
M3 - Conference contribution
C2 - 16447961
AN - SCOPUS:33745483828
SN - 0769523447
SN - 9780769523446
T3 - Proceedings - 2005 IEEE Computational Systems Bioinformatics Conference, CSB 2005
SP - 44
EP - 55
BT - Proceedings - 2005 IEEE Computational SystemsBioinformatics Conference, CSB 2005
PB - IEEE Computer Society
T2 - 2005 IEEE Computational Systems Bioinformatics Conference, CSB 2005
Y2 - 8 August 2005 through 11 August 2005
ER -