Mathematics in Computer Science

, Volume 1, Issue 4, pp 655–672

A Tutorial on Computational Cluster Analysis with Applications to Pattern Discovery in Microarray Data

Authors

    • Dipartimento di Matematica ed ApplicazioniUniversitá di Palermo
  • Davide Scaturro
    • Dipartimento di Matematica ed ApplicazioniUniversitá di Palermo
  • Filippo Utro
    • Dipartimento di Matematica ed ApplicazioniUniversitá di Palermo
Article

DOI: 10.1007/s11786-007-0025-3

Cite this article as:
Giancarlo, R., Scaturro, D. & Utro, F. Math.comput.sci. (2008) 1: 655. doi:10.1007/s11786-007-0025-3

Abstract.

Microarrays offer unprecedented possibilities for the so-called omic, e.g., genomic and proteomic, research. However, they are also quite challenging data to analyze. The aim of this paper is to provide a short tutorial on the most common approaches used for pattern discovery and cluster analysis as they are currently used for microarrays, in the hope to bring the attention of the Algorithmic Community on novel aspects of classification and data analysis that deserve attention and have potential for high reward.

Mathematics Subject Classification (2000).

Primary 68Q25, 68Q05

Keywords.

Clustering algorithmshypothesis testing in statisticsmicroarrays data analysis

Copyright information

© Springer-Verlag 2008