Title: Cancer profiles by affinity propagation

Authors: D. Soria, J.M. Garibaldi, F. Ambrogi, P. Boracchi, E. Raimondi, E. Biganzoli

Addresses: School of Computer Science, University of Nottingham, Jubilee Campus, Wollaton Road, Nottingham, NG8 1BB, UK. ' School of Computer Science, University of Nottingham, Jubilee Campus, Wollaton Road, Nottingham, NG8 1BB, UK. ' Istituto di Statistica Medica e Biometria 'GA Maccacaro', Universita degli Studi di Milano, Via Venezian 1, 20133 Milano, Italy. ' Istituto di Statistica Medica e Biometria 'GA Maccacaro', Universita degli Studi di Milano, Via Venezian 1, 20133 Milano, Italy. ' Struttura di Statistica e Biometria, Fondazione IRCCS Istituto Nazionale Tumori, Via Venezian 1, 20133 Milano, Italy. ' Istituto di Statistica Medica e Biometria 'GA Maccacaro', Universita degli Studi di Milano, Via Venezian 1, 20133 Milano, Italy; Struttura di Statistica e Biometria, Fondazione IRCCS Istituto Nazionale Tumori, Via Venezian 1, 20133 Milano, Italy

Abstract: The affinity propagation algorithm is applied to various problems of breast and cutaneous tumours subtyping using traditional biologic markers. The algorithm provides a procedure to determine the number of profiles to be considered. Well-known breast cancer case series and cutaneous melanoma were used to compare the results of the affinity propagation with the results obtained with standard algorithms and indexes for the optimal choice of the number of clusters. Results from affinity propagation are consistent with the results already obtained having the advantage of providing an indication about the number of clusters.

Keywords: affinity propagation; clustering algorithms; breast cancer; cutaneous melanoma; cancer profiles; tumours; biological markers; biomarkers.

DOI: 10.1504/IJKESDP.2009.028814

International Journal of Knowledge Engineering and Soft Data Paradigms, 2009 Vol.1 No.3, pp.195 - 215

Published online: 03 Oct 2009 *

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