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This measure considers the combined intensity and significance of the agreement or disagreement, between two data sources about the same biological entity. The method is applied to the integrated analysis of gene expression and annotation of two gene sets, one from yeast and other from mouse. The potential of the method to generate accurate mechanistic hypothesis is also demonstrated. Specially, negative correlation results pose a new kind of biological hypothesis. Method performance was compared with annotation enrichment methods, and optimal conditions for the superiority of local correlation results are discussed.<\/jats:p><jats:p>Availability: The matlab functions described in this article are available at http:\/\/bioinformatics.musc.edu\/~frpinto\/<\/jats:p><jats:p>Contact: \u00a0almeidaj@musc.edu<\/jats:p><jats:p>Supplementary information: Further information, tables and figures are available at http:\/\/bioinformatics.musc.edu\/~frpinto\/<\/jats:p>","DOI":"10.1093\/bioinformatics\/bti074","type":"journal-article","created":{"date-parts":[[2004,10,28]],"date-time":"2004-10-28T00:23:01Z","timestamp":1098922981000},"page":"1037-1045","source":"Crossref","is-referenced-by-count":5,"title":["Local correlation of expression profiles with gene annotations\u2014proof of concept for a general conciliatory method"],"prefix":"10.1093","volume":"21","author":[{"given":"F. 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