Abstract: An aspect of the present invention is a computer executable method for characterizing, e.g. for diagnostic purposes, utilizing a reference database, a query sample based on the measurements of biological components. The method is characterized in that it comprises the steps of calculating an expression match score (EM-score) indicating the likelihood of having the component level observed in the query sample in each of the sample categories of the reference database, calculating for the components of the sample, using e.g. the EM-score, tissue specificity score (TS-score), that expresses how uniquely a component identifies the query sample as belonging to a certain sample category, calculating, utilizing e.g. the TS-score, overall similarity of the sample in relation to a tissue category of the reference database, and storing at least some resulting characterization data to a memory device or outputting the data to an output device of a computer.

Abstract: An aspect of the present invention is a computer executable method for characterizing, e.g. for diagnostic purposes, utilizing a reference database, a query sample tissue based on the gene expression data of the tissue. The method is characterized in that it comprises the steps of calculating an expression match score (EM-score) indicating the likelihood of having the gene expression level observed in the query sample in each of the tissue categories of the reference database, calculating for the genes of the sample tissue, using e.g. the EM-score, tissue specificity score (TS-score), that expresses how uniquely a gene identifies the query sample as belonging to a certain tissue category, calculating, utilizing e.g. the TS-score, overall similarity of the sample tissue in relation to a tissue category of the reference database, and storing at least some resulting characterization data to a memory device or outputting the data to an output device of a computer.

Abstract: Techniques for estimating genomic health of a sexually reproducing organism. Stored information on hereditary diseases is used to determine a risk for each disease for allele combinations in a specimen, and to determine a degree of severity, wherein the risk and severity are commensurate. For each hereditary disease a risk is determined for the specimen to have the disease from the from the specimen's genotype; a default risk is assigned, if the hereditary disease exhibits Mendelian inheritance and if the specimen is a carrier of the disease. The risk for the hereditary disease is multiplied by an expansive function (e.g., square) of the severity. A statistically representative value of the multiplied risks is calculated, replacing zero values with marginal finite values if the expansive function cannot process zero values.

Abstract: An aspect of the present invention is a computer executable method for characterizing, e.g. for diagnostic purposes, utilizing a reference database, a query sample tissue based on the gene expression data of the tissue. The method is characterized in that it comprises the steps of calculating an expression match score (EM-score) indicating the likelihood of having the gene expression level observed in the query sample in each of the tissue categories of the reference database, calculating for the genes of the sample tissue, using e.g. the EM-score, tissue specificity score (TS-score), that expresses how uniquely a gene identifies the query sample as belonging to a certain tissue category, calculating, utilizing e.g. the TS-score, overall similarity of the sample tissue in relation to a tissue category of the reference database, and storing at least some resulting characterization data to a memory device or outputting the data to an output device of a computer.

Abstract: An aspect of the present invention is a computer executable method for characterizing, e.g. for diagnostic purposes, utilizing a reference database, a query sample tissue based on the gene expression data of the tissue. The method is characterized in that it comprises the steps of calculating an expression match score (EM-score) indicating the likelihood of having the gene expression level observed in the query sample in each of the tissue categories of the reference database, calculating for the genes of the sample tissue, using e.g. the EM-score, tissue specificity score (TS-score), that expresses how uniquely a gene identifies the query sample as belonging to a certain tissue category, calculating, utilizing e.g. the TS-score, overall similarity of the sample tissue in relation to a tissue category of the reference database, and storing at least some resulting characterization data to a memory device or outputting the data to an output device of a computer.

Abstract: An aspect of the present invention is a computer executable method for characterizing, e.g. for diagnostic purposes, utilizing a reference database, a query sample tissue based on the gene expression data of the tissue. The method is characterized in that it comprises the steps of calculating an expression match score (EM-score) indicating the likelihood of having the gene expression level observed in the query sample in each of the tissue categories of the reference database, calculating for the genes of the sample tissue, using e.g. the EM-score, tissue specificity score (TS-score), that expresses how uniquely a gene identifies the query sample as belonging to a certain tissue category, calculating, utilizing e.g. the TS-score, overall similarity of the sample tissue in relation to a tissue category of the reference database, and storing at least some resulting characterization data to a memory device or outputting the data to an output device of a computer.

Abstract: A computer-implemented method and apparatus for correcting data sets from microarray measurements of gene expression values made with several different microarray versions. The method comprises obtaining data sets (210) of expression values of several genes of biological samples (202), made with several different microarray versions; normalizing (212) the data sets; determining a first gene-specific distribution parameter (220) for each microarray version and a second gene-specific distribution parameter (222) for a combination of microarray versions; determining a gene-specific correction element (226) for each microarray version based on the discrepancy (224) between the first and second gene-specific distribution parameters; correcting a gene's expression value with the gene-specific correction element (226) for the microarray version on which the gene's expression value is based; and storing (118) the gene's corrected expression value (228) in a physical memory (230).