TY - JOUR AU - Demichelis, Francesca AU - Magni, Paolo AU - Piergiorgi, Paolo AU - Rubin, Mark A. AU - Bellazzi, Riccardo PY - 2006 DA - 2006/11/24 TI - A hierarchical Naïve Bayes Model for handling sample heterogeneity in classification problems: an application to tissue microarrays JO - BMC Bioinformatics SP - 514 VL - 7 IS - 1 AB - Uncertainty often affects molecular biology experiments and data for different reasons. Heterogeneity of gene or protein expression within the same tumor tissue is an example of biological uncertainty which should be taken into account when molecular markers are used in decision making. Tissue Microarray (TMA) experiments allow for large scale profiling of tissue biopsies, investigating protein patterns characterizing specific disease states. TMA studies deal with multiple sampling of the same patient, and therefore with multiple measurements of same protein target, to account for possible biological heterogeneity. The aim of this paper is to provide and validate a classification model taking into consideration the uncertainty associated with measuring replicate samples. SN - 1471-2105 UR - https://doi.org/10.1186/1471-2105-7-514 DO - 10.1186/1471-2105-7-514 ID - Demichelis2006 ER -