Neural Networks
A Recurrent Self-Organizing Map for Temporal Sequence Processing
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Hi-index | 0.00 |
A circular Self-Organising Map (SOM) based on a temporal metric has been proposed for clustering and characterising gene expressions. Expression profiles are first modelled with Radial Basis Functions. The co-expression coefficient, defined as the uncentred correlation of the differentiation of the models, is combined in a circular SOM for grouping and ordering the modelled expressions based on their temporal properties. In the proposed method the topology has been extended to temporal and cyclic ordering of the expressions. An example and a test on a microarray dataset are presented to demonstrate the advantages of the proposed method.