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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.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>We propose an extension of the well-known Na\u00efve Bayes classifier, which accounts for biological heterogeneity in a probabilistic framework, relying on Bayesian hierarchical models. The model, which can be efficiently learned from the training dataset, exploits a closed-form of classification equation, thus providing no additional computational cost with respect to the standard Na\u00efve Bayes classifier. We validated the approach on several simulated datasets comparing its performances with the Na\u00efve Bayes classifier. Moreover, we demonstrated that explicitly dealing with heterogeneity can improve classification accuracy on a TMA prostate cancer dataset.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>The proposed Hierarchical Na\u00efve Bayes classifier can be conveniently applied in problems where within sample heterogeneity must be taken into account, such as TMA experiments and biological contexts where several measurements (replicates) are available for the same biological sample. The performance of the new approach is better than the standard Na\u00efve Bayes model, in particular when the within sample heterogeneity is different in the different classes.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-7-514","type":"journal-article","created":{"date-parts":[[2006,11,24]],"date-time":"2006-11-24T19:16:22Z","timestamp":1164395782000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":52,"title":["A hierarchical Na\u00efve Bayes Model for handling sample heterogeneity in classification problems: an application to tissue microarrays"],"prefix":"10.1186","volume":"7","author":[{"given":"Francesca","family":"Demichelis","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paolo","family":"Magni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paolo","family":"Piergiorgi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark A","family":"Rubin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Riccardo","family":"Bellazzi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2006,11,24]]},"reference":[{"issue":"12","key":"1253_CR1","doi-asserted-by":"publisher","first-page":"1462","DOI":"10.1016\/j.humpath.2004.09.009","volume":"35","author":"TJ Browne","year":"2004","unstructured":"Browne TJ, Hirsch MS, Brodsky G, Welch WR, Loda MF, Rubin MA: Prospective evaluation of AMACR (P504S) and basal cell markers in the assessment of routine prostate needle biopsy specimens. 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