Predicting protein-protein interactions with k-Nearest Neighbors classification algorithm (Contributo in atti di convegno)

Type

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

Label

• Predicting protein-protein interactions with k-Nearest Neighbors classification algorithm (Contributo in atti di convegno) (literal)

Anno

• 2010-01-01T00:00:00+01:00 (literal)

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

• 10.1007/978-3-642-14571-1_10 (literal)

Alternative label

• Mario Rosario Guarracino 1; Adriano Nebbia 1 (2010)
  Predicting protein-protein interactions with k-Nearest Neighbors classification algorithm
  in 6th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2009), Genova, 2009
  (literal)

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

• Mario Rosario Guarracino 1; Adriano Nebbia 1 (literal)

Pagina inizio

• 139 (literal)

Pagina fine

• 150 (literal)

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

• Computational Intelligence Methods for Bioinformatics and Biostatistics (literal)

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

• 6160 (literal)

Note

• ISI Web of Science (WOS) (literal)
• Scopu (literal)

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

• 1. CNR - Istituto di Calcolo e Reti ad Alte Prestazioni (ICAR), Napoli, IT, Italia (literal)

Titolo

• Predicting protein-protein interactions with k-Nearest Neighbors classification algorithm (literal)

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

• 978-3-642-14570-4 (literal)

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

• Francesco Masulli; Leif E. Peterson; Roberto Tagliaferri (literal)

Abstract

• In this work we address the problem of predicting proteinprotein interactions. Its solution can give greater insight in the study of complex diseases, like cancer, and provides valuable information in the study of active small molecules for new drugs, limiting the number of molecules to be tested in laboratory. We model the problem as a binary classification task, using a suitable coding of the amino acid sequences. We apply k-Nearest Neighbors classification algorithm to the classes of interacting and noninteracting proteins. Results show that it is possible to achieve high prediction accuracy in cross validation. A case study is analyzed to show it is possible to reconstruct a real network of thousands interacting proteins with high accuracy on standard hardware. (literal)

Editore

• Springer (Editore)
• Springer-Verlag (Editore)

Prodotto di

• Strumenti Integrati di Supporto per le Scienze ‘Omiche’ (INT.P02.005.001) (Modulo)
• Institute for high performance computing and networking (ICAR) (Istituto)

Autore CNR

• MARIO ROSARIO GUARRACINO (Unità di personale interno)

Insieme di parole chiave

• Keywords of "Predicting protein-protein interactions with k-Nearest Neighbors classification algorithm" (Insieme di parole chiave)

Incoming links:

Prodotto

• Institute for high performance computing and networking (ICAR) (Istituto)
• Strumenti Integrati di Supporto per le Scienze ‘Omiche’ (INT.P02.005.001) (Modulo)

Autore CNR di

• MARIO ROSARIO GUARRACINO (Unità di personale interno)

Editore di

• Springer (Editore)
• Springer-Verlag (Editore)

Insieme di parole chiave di

• Keywords of "Predicting protein-protein interactions with k-Nearest Neighbors classification algorithm" (Insieme di parole chiave)