A computer-implemented method for identifying a set having a relationship between a plurality i of bioinformatics data samples of each of a plurality of measurement variables g, based on a ranking method for sorting said data, said relationship being indicative of a biological state, said computer-implemented method comprising sorting the bioinformatics data into an ordered list l according to the ranking provided by the ranking method; characterized in that the computer-implemented method further comprises computing an exchangeability score of pairs of variables of the ordered bioinformatics data, wherein the exchangeability score is a similarity measure for the variables, and the subsets of variables are pairs of variables with an exchangeability score exceeding a predefined threshold value, resulting in an exchangeability matrix V l that carries information about the exchangeability between each of the plurality of measurement variables g such that the entry ( V l) ij of the exchangeability matrix V l is the exchangeability score of measurement variables g i and g j; expanding the ordered list l of the data by multiplying the computed exchangeability matrix V l with a computed diagonal matrix A l comprising information of the position of the variables in the ordered list l to obtain a representation of the ordered list as an expanded experimental list vector l l; and comparing the expanded experimental list vector l l with another list vector comprising a plurality of measurement variables g by computing a dissimilarity score between the expanded experimental list vector l l and the list vector comprising a plurality of measurement variables g resulting in a list of dissimilarity scores, each dissimilarity score corresponding to a specific set of measurement variables g; and determining the relationship between the samples by identifying the specific set of measurement variables g having the smallest dissimilarity score and/or the specific set of measurement variables g having the largest dissimilarity score, thereby reducing the plurality i into an identified set of data samples being indicative of the biological state. sorting the bioinformatics data into an ordered list l according to the ranking provided by the ranking method; characterized in that the computer-implemented method further comprises computing an exchangeability score of pairs of variables of the ordered bioinformatics data, wherein the exchangeability score is a similarity measure for the variables, and the subsets of variables are pairs of variables with an exchangeability score exceeding a predefined threshold value, resulting in an exchangeability matrix V l that carries information about the exchangeability between each of the plurality of measurement variables g such that the entry ( V l) ij of the exchangeability matrix V l is the exchangeability score of measurement variables g i and g j; expanding the ordered list l of the data by multiplying the computed exchangeability matrix V l with a computed diagonal matrix A l comprising information of the position of the variables in the ordered list l to obtain a representation of the ordered list as an expanded experimental list vector l l; and comparing the expanded experimental list vector l l with another list vector comprising a plurality of measurement variables g by computing a dissimilarity score between the expanded experimental list vector l l and the list vector comprising a plurality of measurement variables g resulting in a list of dissimilarity scores, each dissimilarity score corresponding to a specific set of measurement variables g; and determining the relationship between the samples by identifying the specific set of measurement variables g having the smallest dissimilarity score and/or the specific set of measurement variables g having the largest dissimilarity score, thereby reducing the plurality i into an identified set of data samples being indicative of the biological state.