title: HOODS: finding context-specific neighborhoods of proteins, chemicals and diseases.
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.
authors.affiliation: 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.
authors.forename: Albert
authors.initials: A
authors.lastname: Palleja
authors.affiliation: The Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen N , Denmark.
authors.forename: Lars J
authors.initials: LJ
authors.lastname: Jensen
keywords: Algorithm; Context-specific groups; Disease network; Kinase inhibitors; Neighborhoods; Protein interaction network; Small-molecule compounds