Por favor, use este identificador para citar o enlazar este ítem: http://repositorio.itm.edu.co/jspui/handle/itm/246
Tipo documento: info:eu-repo/semantics/masterThesis
Título : Prediction of protein-protein interactions through support vector machines
Autor : Arango Rodríguez, Julián D.
metadata.dc.contributor.advisor: Jaramillo Garzón, Jorge A.
Autor : Jaramillo Garzón, Jorge A.
Arango Rodríguez, Julián D.
Resumen : In this paper, a SVM-based method is implemented for the prediction of protein-protein interactions. This model is initially trained with a set of over 69.000 pairs of protein se-quences based on documented positive interactions. Then, a cross-validation method is performed for estimating the accuracy of the system, showing acceptable performances in terms of sensitivity, specificity and geometric mean. The results are approximately balanced and the overall perfor-mance if around 70% classified through a pairwise kernel and the parameters are set through an particle swarm opti-mization meta-heuristic and showing promising results for the field of bioinformatics.
Palabras clave : INGENIERIA BIOMEDICA
BIOINFORMATICA
PROTEINAS
metadata.dc.format.extent: 5 p.
URI : http://repositorio.itm.edu.co/jspui/handle/itm/246
Aparece en las colecciones: Ingeniería Biomédica (trabajo de grado)

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