Title

Authors

Affiliation

Samsung Electronics Co., Ltd. 416, Maetan 3-dong, Yeongtong-gu, Suwon-si, Gyeonggi-do, 442-742 Korea.

Email

gangman.yi@gmail.com; *Corresponding author

Article Type

Hypothesis

Date

Received October 16, 2011; Accepted October 24, 2011; Published October 31, 2011

Identifying genomic regions that descended from a common ancestor helps us study the gene function and genome evolution. In distantly related genomes, clusters of homologous gene pairs are evidently used in function prediction, operon detection, etc. Currently, there are many kinds of computational methods that have been proposed defining gene clusters to identify gene families and operons. However, most of those algorithms are only available on a data set of small size. We developed an efficient gene clustering algorithm that can be applied on hundreds of genomes at the same time. This approach allows for large-scale study of evolutionary relationships of gene clusters and study of operon formation and destruction. An analysis of proposed algorithms shows that more biological insight can be obtained by analyzing gene clusters across hundreds of genomes, which can help us understand operon occurrences, gene orientations and gene rearrangements.

Citation

Gangman Yi & Jaehee Jung, Bioinformation 7(5): 251-256 (2011)
 

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.