Opened Access LSL: A new measure to evaluate triclusters


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Autor: Gutiérrez Avilés, David
Rubio Escudero, Cristina
Departamento: Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Fecha: 2014
Publicado en: BIBM 2014: IEEE International Conference on Bioinformatics and Biomedicine (2014), p 30-37
ISBN/ISSN: 978-1-4799-5669-2
Tipo de documento: Ponencia
Resumen: Microarray technology has led to a great advance in biological studies due to its ability to monitorize the RNA levels of a vast amount of genes under certain experimental conditions. The use of computational techniques to mine hidden knowledge from these data is of great interest in research fields such as Data Mining and Bioinformatics. Finding patterns of genetic behavior not only taking into account the experimental conditions but also the time condition is a very challenging task nowadays. Clustering, biclustering and novel triclustering techniques offer a very suitable framework to solve the suggested problem. In this work we present LSL, a measure to evaluate the quality of triclusters found in 3D data.
Cita: Gutiérrez Avilés, D. y Rubio Escudero, C. (2014). LSL: A new measure to evaluate triclusters. En BIBM 2014: IEEE International Conference on Bioinformatics and Biomedicine (30-37), Belfast, UK: IEEE Computer Society.
Tamaño: 380.9Kb
Formato: PDF


DOI: 10.1109/BIBM.2014.6999244

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