Abstract

GARCIA BRIZUELA, Jorge; SANTIESTEBAN-TOCA, Cosme E.  and  CAPDESUNER RUIZ, Yanelis. Heuristic determination of relations between the structures and the production of secondary metabolites. Rev cuba cienc informat [online]. 2017, vol.11, n.3, pp. 50-63. ISSN 2227-1899.

ABSTRACT The tobacco culture and production, especially in tropical countries, is highly dependent of pesticides. But, the application of pesticides is often ineffective and dangerous to the humans and the environment. Moreover, it is well known that some secondary metabolites play an essential role in the protection of plants against pathogens. However, establishing the relationship between the production of secondary metabolites and the phonotypical traits requires an extensive experimentation and manual tracking information. Moreover, from the metabolite profile of a particular plant we can derive its biological activity, but it is impossible to deduce the exact metabolic profile of plants according to their biological activity. Therefore, the objective of this research is to design a method based on machine learning techniques, trained on the plants phenotypic profile, which is able to learn the correlation between the secondary metabolites and phenotypic traits of tobacco plants. Finding the relationship between phenotypes and the expression level of a given metabolite, is a regression problem. For this reason, some traditional statistics techniques and machine learning techniques were employed. As a result of experimentation, it was determined that the use of a REPTree regression tree, determines the characteristics that best correlate with the studied metabolite. Also, as an added value, it is able to return a set of simple rules that describe this process.

Keywords : correlation; metabolites; phenotypes; regression.

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