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Traditional data management approaches need to be leveraged to support scientific discovery. A query language that supports biological science must be capable of expressing and implementing biological investigations. The biological query language (BQL) presented in this paper aims to enhance the scientists querying ability by: (1) providing an intermediate query language between scientific workflows and traditional query languages such as SQL, (2) expressing operators such as ranking and validating, not made directly available by traditional query languages and often difficult to express (by complex queries), and (3) constraining the evaluation of their operators by various semantics. This paper shows step by step how the overall problem of identifying genes related to a disease may be translated into a succession of BQL queries.