Cluster analysis of biological networks

Asuda Sharma, Hesham Ali, Dario Ghersi

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Clustering methods are widely used as a first step for taming the complexity of biological networks and for extracting information from them. However, the bewildering number of available clustering algorithms and the lack of agreed upon validity measures represent a major challenge for the user, as no one-size-fits-all solution to the clustering problem exists. This article surveys the main types of clustering algorithms, highlighting their strengths and weaknesses when used for clustering biological data. We also discuss internal and external validity measures, emphasizing the importance of domain knowledge for choosing an appropriate clustering approach.

Original languageEnglish (US)
Title of host publicationEncyclopedia of Bioinformatics and Computational Biology
Subtitle of host publicationABC of Bioinformatics
PublisherElsevier
Pages1036-1046
Number of pages11
Volume1-3
ISBN (Electronic)9780128114322
ISBN (Print)9780128114148
DOIs
StatePublished - Jan 1 2018

Keywords

  • Biological networks
  • Cluster analysis
  • Clustering methods
  • External validation
  • Internal validation
  • Validity of clusters

ASJC Scopus subject areas

  • Medicine(all)

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