HOODS: finding context-specific neighborhoods of proteins, chemicals and diseases.
PeerJ
; 3: e1057, 2015.
Article
em En
| MEDLINE
| ID: mdl-26157625
ABSTRACT
Clustering algorithms are often used to find groups relevant in a specific context; however, they are not informed about this context. We present a simple algorithm, HOODS, which identifies context-specific neighborhoods of entities from a similarity matrix and a list of entities specifying the context. We illustrate its applicability by finding disease-specific neighborhoods of functionally associated proteins, kinase-specific neighborhoods of structurally similar inhibitors, and physiological-system-specific neighborhoods of interconnected diseases. HOODS can be used via a simple interface at http//hoods.jensenlab.org, from where the source code can also be downloaded.
Texto completo:
1
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Revista:
PeerJ
Ano de publicação:
2015
Tipo de documento:
Article
País de afiliação:
Dinamarca