Catálogo de publicaciones - libros
Analisi matematica I: Teoria ed esercizi con complementi in rete
Claudio Canuto Anita Tabacco
2a edizione.
Resumen/Descripción – provisto por la editorial
No disponible.
Palabras clave – provistas por la editorial
Analysis; Fourier Analysis
Disponibilidad
| Institución detectada | Año de publicación | Navegá | Descargá | Solicitá |
|---|---|---|---|---|
| No detectada | 2005 | SpringerLink |
Información
Tipo de recurso:
libros
ISBN impreso
978-88-470-0337-8
ISBN electrónico
978-88-470-0400-9
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
2005
Información sobre derechos de publicación
© Springer-Verlag Milan 2005
Cobertura temática
Tabla de contenidos
Nozioni di base
Claudio Canuto; Anita Tabacco
Gene set enrichment analysis is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. In this paper we present a novel method integrating gene interaction information with Gene Ontology (GO) for the construction of new interesting enriched gene sets. The experimental results show that the introduced method improves over traditional methods that compute the enrichment of a single GO terms, i.e. that it is capable to find new statistically relevant descriptions of the biology governing the experiments not detectable by the existing methods.
Pp. 1-31
Funzioni
Claudio Canuto; Anita Tabacco
Gene set enrichment analysis is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. In this paper we present a novel method integrating gene interaction information with Gene Ontology (GO) for the construction of new interesting enriched gene sets. The experimental results show that the introduced method improves over traditional methods that compute the enrichment of a single GO terms, i.e. that it is capable to find new statistically relevant descriptions of the biology governing the experiments not detectable by the existing methods.
Pp. 33-66
Limiti e continuità I
Claudio Canuto; Anita Tabacco
Gene set enrichment analysis is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. In this paper we present a novel method integrating gene interaction information with Gene Ontology (GO) for the construction of new interesting enriched gene sets. The experimental results show that the introduced method improves over traditional methods that compute the enrichment of a single GO terms, i.e. that it is capable to find new statistically relevant descriptions of the biology governing the experiments not detectable by the existing methods.
Pp. 67-90
Limiti e continuità II
Claudio Canuto; Anita Tabacco
Gene set enrichment analysis is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. In this paper we present a novel method integrating gene interaction information with Gene Ontology (GO) for the construction of new interesting enriched gene sets. The experimental results show that the introduced method improves over traditional methods that compute the enrichment of a single GO terms, i.e. that it is capable to find new statistically relevant descriptions of the biology governing the experiments not detectable by the existing methods.
Pp. 91-125
Confronto locale di funzioni. Successioni e serie numeriche
Claudio Canuto; Anita Tabacco
Gene set enrichment analysis is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. In this paper we present a novel method integrating gene interaction information with Gene Ontology (GO) for the construction of new interesting enriched gene sets. The experimental results show that the introduced method improves over traditional methods that compute the enrichment of a single GO terms, i.e. that it is capable to find new statistically relevant descriptions of the biology governing the experiments not detectable by the existing methods.
Pp. 127-169
Calcolo differenziale
Claudio Canuto; Anita Tabacco
Gene set enrichment analysis is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. In this paper we present a novel method integrating gene interaction information with Gene Ontology (GO) for the construction of new interesting enriched gene sets. The experimental results show that the introduced method improves over traditional methods that compute the enrichment of a single GO terms, i.e. that it is capable to find new statistically relevant descriptions of the biology governing the experiments not detectable by the existing methods.
Pp. 171-228
Sviluppi di Taylor e applicazioni
Claudio Canuto; Anita Tabacco
Gene set enrichment analysis is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. In this paper we present a novel method integrating gene interaction information with Gene Ontology (GO) for the construction of new interesting enriched gene sets. The experimental results show that the introduced method improves over traditional methods that compute the enrichment of a single GO terms, i.e. that it is capable to find new statistically relevant descriptions of the biology governing the experiments not detectable by the existing methods.
Pp. 229-263
Rappresentazioni del piano e dello spazio
Claudio Canuto; Anita Tabacco
Gene set enrichment analysis is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. In this paper we present a novel method integrating gene interaction information with Gene Ontology (GO) for the construction of new interesting enriched gene sets. The experimental results show that the introduced method improves over traditional methods that compute the enrichment of a single GO terms, i.e. that it is capable to find new statistically relevant descriptions of the biology governing the experiments not detectable by the existing methods.
Pp. 265-307
Calcolo integrale I
Claudio Canuto; Anita Tabacco
Gene set enrichment analysis is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. In this paper we present a novel method integrating gene interaction information with Gene Ontology (GO) for the construction of new interesting enriched gene sets. The experimental results show that the introduced method improves over traditional methods that compute the enrichment of a single GO terms, i.e. that it is capable to find new statistically relevant descriptions of the biology governing the experiments not detectable by the existing methods.
Pp. 309-365
Calcolo integrale II
Claudio Canuto; Anita Tabacco
Gene set enrichment analysis is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. In this paper we present a novel method integrating gene interaction information with Gene Ontology (GO) for the construction of new interesting enriched gene sets. The experimental results show that the introduced method improves over traditional methods that compute the enrichment of a single GO terms, i.e. that it is capable to find new statistically relevant descriptions of the biology governing the experiments not detectable by the existing methods.
Pp. 367-398