Ponencia
Gene–Gene Interaction based Clustering method for Microarray Data
Autor/es | Díaz Díaz, Norberto
Gómez Vela, Francisco Aguilar Ruiz, Jesús García Gutiérrez, Jorge |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2011 |
Fecha de depósito | 2022-12-12 |
Publicado en |
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ISBN/ISSN | 978-1-4577-1676-8 2164-7143 2164-7151 |
Resumen | In this paper, we propose a greedy clustering
algorithm to identify groups of related genes and a new
measure to improve the results of this algorithm. Clustering
algorithms analyze genes in order to group those with ... In this paper, we propose a greedy clustering algorithm to identify groups of related genes and a new measure to improve the results of this algorithm. Clustering algorithms analyze genes in order to group those with similar behavior. Instead, our approach groups pairs of genes that present similar positive and/or negative interactions. In order to avoid noise in clusters, we apply a threshold, the neighbouring minimun index(λ), to know if a pair of genes have interac tion enough or not. The algorithm allows the researcher to modify all the criteria: discretization mapping function, gene– gene mapping function and filtering function, and even the neighbouring minimun index, and provides much flexibility to obtain clusters based on the level of precision needed. We have carried out a deep experimental study in databases to obtain a good neighbouring minimun index, λ. The performance of our approach is experimentally tested on the yeast, yeast cell-cycle and malaria datasets. The final number of clusters has a very high level of customization and genes within show a significant level of cohesion, as it is shown graphically in the experiments |
Cita | Díaz Díaz, N., Gómez Vela, F., Aguilar Ruiz, J. y García Gutiérrez, J. (2011). Gene–Gene Interaction based Clustering method for Microarray Data. En ISDA 2011: 11th International Conference on Intelligent Systems Design and Applications (1067-1073), Córdoba, España: IEEE Computer Society. |
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