Data/hora: 20/05/2024 05:31:29

Provedor de dados: 	74	
País: 	Brazil	
Título: 	Evaluation of noise reduction techniques in the splice junction recognition problem	
Autores: 	Lorena,Ana C.; Carvalho,André C. P. L. F. de.	
Data: 	2004-01-01	
Ano: 	2004	
Palavras-chave: 	Pre-processing; Machine learning; Splice junction recognition.	
Resumo: 	The Human Genome Project has generated a large amount of sequence data. A number of works are currently concerned with analyzing these data. One of the analyses carried out is the identification of genes' structures on the sequences obtained. As such, one can search for particular signals associated with gene expression. Splice junctions represent a type of signal present on eukaryote genes. Many studies have applied Machine Learning techniques in the recognition of such regions. However, most of the genetic databases are characterized by the presence of noisy data, which can affect the performance of the learning techniques. This paper evaluates the effectiveness of five data pre-processing algorithms in the elimination of noisy instances from two splice junction recognition datasets. After the pre-processing phase, two learning techniques, Decision Trees and Support Vector Machines, are employed in the recognition process.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572004000400031	
Editor: 	Sociedade Brasileira de Genética	
Relação: 	10.1590/S1415-47572004000400031	
Formato: 	text/html	
Fonte: 	Genetics and Molecular Biology  v.27 n.4 2004	
Fonte: 	info:eu-repo/semantics/openAccess