Context-Aware Visual Exploration of Molecular Databases (Contributo in atti di convegno)

Type

• Contributo in atti di convegno (Classe)
• Prodotto della ricerca (Classe)

Label

• Context-Aware Visual Exploration of Molecular Databases (Contributo in atti di convegno) (literal)

Anno

• 2006-01-01T00:00:00+01:00 (literal)

Alternative label

• Di Fatta Giuseppe, Fiannaca Antonino, Rizzo Riccardo, Urso Alfonso, Berthold Michael R., Gaglio Salvatore (2006)
  Context-Aware Visual Exploration of Molecular Databases
  in IEEE ICDM 2006 Workshop on Data Mining in Bioinformatics, Hong Kong, 18-22 December
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Di Fatta Giuseppe, Fiannaca Antonino, Rizzo Riccardo, Urso Alfonso, Berthold Michael R., Gaglio Salvatore (literal)

Pagina inizio

• 136 (literal)

Pagina fine

• 141 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url

• http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.51 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume

• Proceedings - IEEE International Conference on Data Mining, ICDM (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali

• 5 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• 1 - University of Reading, 2,3,4 - ICAR CNR, 6- Universita' di Palermo (literal)

Titolo

• Context-Aware Visual Exploration of Molecular Databases (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn

• 0-7695-2702-7 (literal)

Abstract

• Facilitating the visual exploration of scientific data has received increasing attention in the past decade or so. Especially in life science related application areas the amount of available data has grown at a breath taking pace. In this paper we describe an approach that allows for visual inspection of large collections of molecular compounds. In contrast to classical visualizations of such spaces we incorporate a specific focus of analysis, for example the outcome of a biological experiment such as high throughout screening results. The presented method uses this experimental data to select molecular fragments of the underlying molecules that have interesting properties and uses the resulting space to generate a two dimensional map based on a singular value decomposition algorithm and a self-organizing map. Experiments on real datasets show that the resulting visual landscape groups molecules of similar chemical properties in densely connected regions (literal)

Editore

• IEEE Computer Society (Editore)

Prodotto di

• Institute for high performance computing and networking (ICAR) (Istituto)

Autore CNR

• RICCARDO RIZZO (Persona)
• ALFONSO URSO (Unità di personale interno)
• ANTONINO FIANNACA (Unità di personale esterno)

Incoming links:

Prodotto

• Institute for high performance computing and networking (ICAR) (Istituto)

Autore CNR di

• ALFONSO URSO (Unità di personale interno)
• RICCARDO RIZZO (Persona)
• ANTONINO FIANNACA (Unità di personale esterno)

Editore di

• IEEE Computer Society (Editore)