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BioMed Research International
Volume 2014 (2014), Article ID 145243, 14 pages
http://dx.doi.org/10.1155/2014/145243
Research Article

Integration of High-Volume Molecular and Imaging Data for Composite Biomarker Discovery in the Study of Melanoma

1Department of Computer Science and Biomedical Informatics, University of Thessaly, Papasiopoulou 2-4, 35100 Lamia, Greece
2Department of Digital Systems, University of Piraeus, Grigoriou Lampraki 126, 18532 Piraeus, Greece
3Metabolic Engineering and Bioinformatics Programme, Institute of Biology, Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, 48 Vasileos Constantinou Avenue, 11635 Athens, Greece

Received 29 April 2013; Revised 28 September 2013; Accepted 12 October 2013; Published 16 January 2014

Academic Editor: Hesham H. Ali

Copyright © 2014 Konstantinos Moutselos et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supplementary Material

Paragraph description for Supplementary 1: PCA representations for the 6 different datasets, classifying melanomas from healthy donors, namely 2 datasets corresponding toeither the microarray(o.m) or the dermoscopic data(o.i), plus 4 integrated datasets, applying the missing value imputation schemes, defined in page 5.

Paragraph description for Supplementary 2: LDA representations for the 6 different datasets, classifying melanomas from healthy donors, namely 2 datasets corresponding to either microarray (o.m) or dermoscopic data (o.i), plus 4 integrated datasets, applying the missing value imputation schemes, defined in page 5.

  1. Supplementary Materials
  2. Supplementary Materials