Apcluster: An R package for affinity propagation clustering

Ulrich Bodenhofer; Andreas Kothmeier; Sepp Hochreiter

doi:10.1093/bioinformatics/btr406

Apcluster: An R package for affinity propagation clustering

Ulrich Bodenhofer, Andreas Kothmeier, Sepp Hochreiter

Research output: Contribution to journal › Article › peer-review

347 Citations (Scopus)

Abstract

SUMMARY: Affinity propagation (AP) clustering has recently gained increasing popularity in bioinformatics. AP clustering has the advantage that it allows for determining typical cluster members, the so-called exemplars. We provide an R implementation of this promising new clustering technique to account for the ubiquity of R in bioinformatics. This article introduces the package and presents an application from structural biology.

AVAILABILITY: The R package apcluster is available via CRAN-The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/apcluster

CONTACT: [email protected]; [email protected].

Original language	English
Article number	btr406
Pages (from-to)	2463-2464
Number of pages	2
Journal	Bioinformatics
Volume	27
Issue number	17
DOIs	https://doi.org/10.1093/bioinformatics/btr406
Publication status	Published - Sept 2011
Externally published	Yes

Keywords

Algorithms
Amino Acid Motifs
Cluster Analysis
Computational Biology/methods
Sequence Analysis, Protein
Software

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10.1093/bioinformatics/btr406

Cite this

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abstract = "SUMMARY: Affinity propagation (AP) clustering has recently gained increasing popularity in bioinformatics. AP clustering has the advantage that it allows for determining typical cluster members, the so-called exemplars. We provide an R implementation of this promising new clustering technique to account for the ubiquity of R in bioinformatics. This article introduces the package and presents an application from structural biology.AVAILABILITY: The R package apcluster is available via CRAN-The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/apclusterCONTACT: [email protected]; [email protected].",

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author = "Ulrich Bodenhofer and Andreas Kothmeier and Sepp Hochreiter",

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doi = "10.1093/bioinformatics/btr406",

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N2 - SUMMARY: Affinity propagation (AP) clustering has recently gained increasing popularity in bioinformatics. AP clustering has the advantage that it allows for determining typical cluster members, the so-called exemplars. We provide an R implementation of this promising new clustering technique to account for the ubiquity of R in bioinformatics. This article introduces the package and presents an application from structural biology.AVAILABILITY: The R package apcluster is available via CRAN-The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/apclusterCONTACT: [email protected]; [email protected].

AB - SUMMARY: Affinity propagation (AP) clustering has recently gained increasing popularity in bioinformatics. AP clustering has the advantage that it allows for determining typical cluster members, the so-called exemplars. We provide an R implementation of this promising new clustering technique to account for the ubiquity of R in bioinformatics. This article introduces the package and presents an application from structural biology.AVAILABILITY: The R package apcluster is available via CRAN-The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/apclusterCONTACT: [email protected]; [email protected].

KW - Algorithms

KW - Amino Acid Motifs

KW - Cluster Analysis

KW - Computational Biology/methods

KW - Sequence Analysis, Protein

KW - Software

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ER -

Apcluster: An R package for affinity propagation clustering

Abstract

Keywords

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