An adaptive approach for integration analysis of multiple gene expression datasets
AIMSA'10 Proceedings of the 14th international conference on Artificial intelligence: methodology, systems, and applications
Clustering of multiple microarray experiments using information integration
ITBAM'11 Proceedings of the Second international conference on Information technology in bio- and medical informatics
Hybrid method for the analysis of time series gene expression data
Knowledge-Based Systems
| Hi-index | 3.84 |
Summary: A novel integration approach targeting the combination of multi-experiment time series expression data is proposed. A recursive hybrid aggregation algorithm is initially employed to extract a set of genes, which are eventually of interest for the biological phenomenon under study. Next, a hierarchical merge procedure is speci.cally developed for the purpose of fusing together the multiple-experiment expression pro.les of the selected genes. This employs dynamic time warping alignment techniques in order to account adequately for the potential phase shift between the different experiments. We subsequently demonstrate that the resulting gene expression pro.les consistently re.ect the behavior of the original expression pro.les in the different experiments. Contact: vboeva@tu-plovdiv.bg Supplementary information: Supplementary data are available at http://www.tu-plovdiv.bg/Container/bi/DataIntegration/