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In general, molecular signatures of diseases are estimated by comparing the two sets of molecular data measured for the samples with distinctive phenotypes, and then molecular functions of the diseases are characterized by the following analyses of the signatures. Unfortunately, ambiguous relationships between molecular signatures and functions are observed in some cases, due to a posteriori justification from molecular level to phenotype level. Here, we propose a method for detecting molecular functions of the disease by a deductive justification from phenotype level to molecular level, and illustrate its performance by applying our method to the gene expression and phenotype data sets for diabetes progression in Goto-Kakizaki rat. By our method, the functions identified by the previous studies were well covered, and furthermore, some implications for molecular mechanisms were obtained. Our phenotype-difference oriented method provides some clues to bridge directly a gap between molecular signatures and phenotype data in diabetes.