Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDE.2009.205
Title: Exploiting domain knowledge to improve biological significance of biclusters with key missing genes
Authors: Chen, J.
Ji, L.
Hsu, W. 
Tan, K.-L. 
Rhee, S.Y.
Issue Date: 2009
Source: Chen, J.,Ji, L.,Hsu, W.,Tan, K.-L.,Rhee, S.Y. (2009). Exploiting domain knowledge to improve biological significance of biclusters with key missing genes. Proceedings - International Conference on Data Engineering : 1219-1222. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDE.2009.205
Abstract: In an era of increasingly complex biological datasets, one of the key steps in gene functional analysis comes rom clustering genes based on co-expression. Biclustering algorithmscan identify gene clusters with local co-expressed patterns, which are more likely to define genes functioning togetherthan global clustering methods. However, these algorithms are not effective in uncovering gene regulatory networks because the mined biclusters lack genes that may be critical in the function but may not be co-expressed with the clustered genes. In this paper, we introduce a biclustering method called SKeleton Biclustering (SKB), which builds high quality biclusters from microarray data, creates relationships among the biclustered genes based on Gene Ontology annotations, and identifies genes that are missing in the biclusters. SKB thus defines inter-bicluster and intra-bicluster functional relationships. The delineation of functional relationships and incorporation of such missing genes may help biologists to discover biological processes that are important in a given study and provides clues for how the processes may be functioning together. Experimental results show that, with SKB, the biological significance of the biclusters is considerably improved. © 2009 IEEE.
Source Title: Proceedings - International Conference on Data Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/40957
ISBN: 9780769535456
ISSN: 10844627
DOI: 10.1109/ICDE.2009.205
Appears in Collections:Staff Publications

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

Page view(s)

41
checked on Dec 16, 2017

Google ScholarTM

Check

Altmetric


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