A computer executable method for characterizing, utilizing a reference database, a query sample based on the gene expression data of the sample characterized in that the method comprises the steps of: a. building expression level density estimates for each gene of a tissue category of the reference database, b. calculating for the genes of the query sample and for a plurality of tissue categories in the reference database an expression match score for each gene with respect to each tissue category indicating the likelihood of having a gene expression level observed in the query sample in each of the tissue categories of the reference database, c. calculating for the genes of the query sample and for a plurality of tissue categories of the reference database, using the expression match score, a tissue specificity score for each gene with respect to each tissue category that expresses how uniquely a gene identifies the query sample as belonging to the tissue category, the tissue specificity score being calculated by comparing the expression match score for the gene for all tissues, d. calculating, using the tissue specificity scores, a tissue similarity score that indicates the overall similarity of the query sample in relation to a tissue category of the reference database, e. storing at least some resulting characterization data comprising at least one identified tissue category identified using the tissue similarity score and/or at least one gene identified using the tissue specificity score or the expression match score to a memory device or outputting the data to an output device of a computer, the at least one identified tissue category characterizing biological properties of the query sample, characterized in that the calculation of the expression match score of a gene of the query sample vis-à-vis a tissue category in the reference database comprises: - comparing the expression value of the gene in the query sample to the density estimate for that same gene in the tissue category in evaluation points being between the minimum and the maximum expression levels of the gene, - identifying a corresponding density value for the gene of the query sample, and - calculating the expression match score to be the fraction of evaluation points having density lower than the density of the query sample. a. building expression level density estimates for each gene of a tissue category of the reference database, b. calculating for the genes of the query sample and for a plurality of tissue categories in the reference database an expression match score for each gene with respect to each tissue category indicating the likelihood of having a gene expression level observed in the query sample in each of the tissue categories of the reference database, c. calculating for the genes of the query sample and for a plurality of tissue categories of the reference database, using the expression match score, a tissue specificity score for each gene with respect to each tissue category that expresses how uniquely a gene identifies the query sample as belonging to the tissue category, the tissue specificity score being calculated by comparing the expression match score for the gene for all tissues, d. calculating, using the tissue specificity scores, a tissue similarity score that indicates the overall similarity of the query sample in relation to a tissue category of the reference database, e. storing at least some resulting characterization data comprising at least one identified tissue category identified using the tissue similarity score and/or at least one gene identified using the tissue specificity score or the expression match score to a memory device or outputting the data to an output device of a computer, the at least one identified tissue category characterizing biological properties of the query sample, - comparing the expression value of the gene in the query sample to the density estimate for that same gene in the tissue category in evaluation points being between the minimum and the maximum expression levels of the gene, - identifying a corresponding density value for the gene of the query sample, and - calculating the expression match score to be the fraction of evaluation points having density lower than the density of the query sample.