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PeerJ. 2015 Jun 30;3:e1057. doi: 10.7717/peerj.1057. eCollection 2015.

HOODS: finding context-specific neighborhoods of proteins, chemicals and diseases.

Author information

1
The Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen N , Denmark ; The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen Ø , Denmark.
2
The Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen N , Denmark.

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.

KEYWORDS:

Algorithm; Context-specific groups; Disease network; Kinase inhibitors; Neighborhoods; Protein interaction network; Small-molecule compounds

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