*omeSOM is a tool designed to give support to the data mining task of metabolic and transcriptional datasets derived from different databases. It provides a user-friendly interface and offers several visualization tools easy to understand by non-expert users. Therefore, *omeSOM is a tool designed to give support to the data mining task applied to basic research as well as breeding programs.

Main features

*omeSOM is oriented towards discovering unknown relationships between data, as well as providing simple visualizations for the identification of co-expressed genes and co-accumulated metabolites. A case study which involved gene expression measurements and metabolite profiles from tomato fruits is provided to show the application of the proposed tool. The interest in comparing the cultivated tomato against the different ILs lies on the fact that, as it has been proven, some wild tomato relatives can be sources of several agronomical characters which could be used for the improvement of commercial tomato lines.


Improving clustering with metabolic pathway data
D. H. Milone, G. Stegmayer, M. López, L. Kamenetzky, F. Carrari
BMC Bioinformatics - 2014
Data Mining Over Biological Datasets: An Integrated Approach Based on Computational Intelligence
G. Stegmayer, M. Gerard, D. H. Milone
IEEE Computational Intelligence Magazine - 2012
A Biologically Inspired Validity Measure for Comparison of Clustering Methods over Metabolic Data Sets
G. Stegmayer, D.H. Milone, L. Kamenetzky, M. López, F. Carrari
IEEE/ACM Transactions on Computational Biology and Bioinformatics - 2012
Source and sample data: GMLC 0.10.10
*omeSOM: a software for clustering and visualization of transcriptional and metabolite data mined from interspecific crosses of crop plants
D. H. Milone, G. Stegmayer, L. Kamenetzky, M. López, Je Min Lee, James J Giovannoni, F. Carrari
BMC Bioinformatics - 2010
Source and sample data: *omeSOM v0.26.13 - Sample Data 2
Analysis and integration of biological data: a data mining approach using neural networks
D. H. Milone, G. Stegmayer, M. Gerard, L. Kamenetzky, M. López, F. Carrari
IGI Global - 2010
Neural Network Model for Integration and Visualization of Introgressed Genome and Metabolite Data
G. Stegmayer, D. H. Milone, L. Kamenetzky, M. López, F. Carrari
IEEE International Joint Conference on Neural Networks (IJCNN) - 2009