Implementación de técnicas de reconocimiento de patrones (Least Square Support Vector Machines) en procesos de selección de parámetros característicos aplicados a sistemas metabolómicos

William Villamizar Rozo; Luis Enrique Mendoza; Pablo Alexander Santafe Gutierrez

doi:10.24054/rcta.v1i21.1897

Autores/as

William Villamizar Rozo Universidad de Pamplona
Luis Enrique Mendoza Universidad de Pamplona
Pablo Alexander Santafe Gutierrez Universidad de Pamplona

DOI:

https://doi.org/10.24054/rcta.v1i21.1897

Palabras clave:

Metabolómica, HNMR, LS-SVM, COW

Resumen

En este artículo se presenta una metodologíaque involucra, técnicas de análisis multivariable y una etapa de pre-procesamiento con el fin de determinar metabolitos característicos en un determinado espectro. Este método novedoso permitió determinar que ciertos metabolitos son modificados por las diferentes concentraciones y además de conocer la funcionalidad de LS-SVM en datos NMR. También se logró validar procesos como: alineamiento de picos, normalización, corrección de línea base y análisis multienergía, en datos metabolómicos en aceites de oliva y avellana puros y mezclados con alteraciones de 2%, 5%, 10%, 20% y 30%.

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