Ten lectures on wavelets
An Invariance Property of Predictors in Kernel-Induced Hypothesis Spaces
Neural Computation
Selection of relevant genes in cancer diagnosis based on their prediction accuracy
Artificial Intelligence in Medicine
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Motivations: A large number of single nucleotide polymorphisms (SNPs) are supposed to be involved in onset, differentiation and development of complex diseases. Univariate analysis is limited in studying complex traits since does not take into account gene-gene interaction, and the correlation of multiple SNPs with a specific phenotype. Moreover it might underestimate gene variants with weaker genetic contribution. Therefore more sophisticated techniques should be adopted when investigating the role of a panel of genetic markers in disease predisposition. Methods: In this paper we describe a general method to simultaneously investigate the association between SNPs profile and Crohn's disease (CD), by evaluating the susceptibility or protective role of single or groups of markers. As an association measure we adopted a weighted linear combination of SNPs in which suitable weighting vectors belonged to predefined and over-complete vocabularies of vectors (frames), or were determined by the data. Results: The proposed method found a weighted linear combination of SNPs statistically associated to CD (p=3.81x10^-^1^0) describing the role of the markers in the pathology. In particular, MCP1-A2518G gave the major contribution as protective locus, similarly to TNF-@a-C857T, DLG5 rs124869, PTPN22 C1858T variants. The NF@kB -94ATTG variants was found to be irrelevant for CD. For the remaining markers, a susceptibility role was attributed also confirming that markers on CARD15 gene, in particular G908R and L1007fsinsC, are involved with CD to the same extent as FcGIIIA G559T and TNF-@a-G308A. Moreover, an odds ratio of 3.99(p