INVESTIGADORES
STEGMAYER Georgina Silvia
congresos y reuniones científicas
Título:
New approach for biological clustering based on Gene Ontology
Autor/es:
G. LEALE, D. MILONE, A. BAYÁ, P. GRANITTO, G. STEGMAYER
Lugar:
Rosario
Reunión:
Congreso; 4to Congreso Argentino de Bioinformática y Biología Computacional; 2013
Institución organizadora:
Asociación Argentina de Bioinformática y Biología Computacional
Resumen:
Clustering algorithms are applied on gene expression data to unravel information about biological processes which are hidden in the data. The knowledge and relations extracted from the data are later validated by the biologists. As a common practice, clustering is performed using Euclidean distance or correlation on gene expression data. This approach does not include explicit biological information in the process. Recently, several semantic measures based on Gene Ontology (GO) have been developed to include direct biological knowledge into similarities. In this work, we propose the combination of both types of distances, which can be used within a clustering algorithm, leading to better results from a biological perspective. The proposal has been tested on two real datasets andvalidated with classical and biological performance measures.
