Abstract
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.
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Möller-Levet, C.S., Yin, H. (2005). Circular SOM for Temporal Characterisation of Modelled Gene Expressions. In: Gallagher, M., Hogan, J.P., Maire, F. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2005. IDEAL 2005. Lecture Notes in Computer Science, vol 3578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11508069_42
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DOI: https://doi.org/10.1007/11508069_42
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