Ahn Jaegyoon, Choi Junhyeok, Kim Harrim, Kim Jibum
1 Department of Computer Science and Engineering, Incheon National University, Incheon, South Korea.
2 Midas Information Technology, Seongnam-si, South Korea.
J Comput Biol. 2019 May;26(5):432-441. doi: 10.1089/cmb.2019.0003. Epub 2019 Feb 25.
Biclustering is a process of finding groups of genes that behave similarly under a subset of conditions. In this article, we propose an efficient biclustering algorithm, namely RN+, to identify biologically meaningful biclusters in gene expression data. The RN+ algorithm finds biologically meaningful biclusters through a novel gene filtering using protein-protein interaction network, gene searching, gene grouping, and queuing process. It also efficiently removes duplicate biclusters. We tested the proposed RN+ on five real microarray datasets, and compared its performance with seven competitive biclustering algorithms. The experimental results show that RN+ efficiently finds functionally enriched and biologically meaningful biclusters for large gene expression datasets, and outperforms the other tested biclustering algorithms on real datasets.
