DiatSOM: A R-package for diatom biotypology using self-organizing maps

Marius Bottin, Jean Luc Giraudel, Sovan Lek, Juliette Tison-Rosebery

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

11 Citas (Scopus)


Owing to the high complexity of diatom community data, there is a special need for methods accounting for complex non-linear gradients. A Kohonen's self-organizing map (SOM) is a neural network with unsupervised learning. It allows both unbiased classification of the communities and visualization of biological gradients on a two-dimensional plane. However, as with other neural networks, many parameters must be set. A new R-package with a SOM parameterization specifically suited to diatom communities has been developed. Further developments will consist of creating a graphical user interface in order to make this method easier to use for the scientific community.

Idioma originalInglés estadounidense
Páginas (desde-hasta)5-9
Número de páginas5
PublicaciónDiatom Research
EstadoPublicada - ene. 2 2014
Publicado de forma externa

Áreas temáticas de ASJC Scopus

  • Ciencias acuáticas


Profundice en los temas de investigación de 'DiatSOM: A R-package for diatom biotypology using self-organizing maps'. En conjunto forman una huella única.

Citar esto