Self-Organizing Maps
Data Mining with Computational Intelligence (Advanced Information and Knowledge Processing)
Data Mining with Computational Intelligence (Advanced Information and Knowledge Processing)
Intelligent Bioinformatics: The Application of Artificial Intelligence Techniques to Bioinformatics Problems
Bioinformatics
An Introduction to Metabolic Networks and Their Structural Analysis
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Computational Intelligence in Bioinformatics
Computational Intelligence in Bioinformatics
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Expert Systems with Applications: An International Journal
An evolutionary approach for searching metabolic pathways
Computers in Biology and Medicine
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The volume of information derived from postgenomic technologies is rapidly increasing. Due to the amount of data involved, novel computational models are needed for introducing order into the massive data sets produced by these new technologies. Data integration is also gaining increasing attention for merging signals in order to discover unknown pathways. These topics require the development of adequate soft computing tools. This work proposes a neural network model for discovering relationships between gene expression and metabolite profiles of introgressed lines. It also provides a simple visualization interface for identification of coordinated variations in mRNA and metabolites. This may be useful when the focus is on the easily identification of groups of different patterns, independently of the number of formed clusters. This kind of analysis may help for the inference of a-priori unknown metabolic pathways involving the grouped data. The model has been used on a case study involving data from tomato fruits.