Abstract: Disclosed are software assisted systems and methods for analyzing biological data sets to generate hypotheses potentially explanatory of the data. Active causative relationships in the biology of complex living systems are discovered by providing a data base of biological assertions comprising a multiplicity of nodes representative of a network of biological entities, actions, functional activities, and concepts, and relationship links between the nodes. Simulating perturbation of individual root nodes in the network initiates a cascade of virtual activity through the relationship links to discern plural branching paths within the data base. Operational data, e.g., experimental data, representative of a real or hypothetical perturbations of one or more nodes are mapped onto the data base. The branching paths then are prioritized as hypotheses on the basis of how well they predict the operational data. Logic based criteria are applied to the graphs to reject graphs as not likely representative of real biology.

Abstract: In one aspect, the invention comprises a method of developing an immunosuppressant drug with reduced propensity to induce type II diabetes mellitus symptoms by assaying candidate molecular entities for binding preferentially to leukocyte isoform calcineurin and less preferentially to muscle cell isoform calcineurin. In another aspect, the invention comprises a method for determining the onset, severity, or response to treatment of post-transplant diabetes mellitus comprising determining from a patient at risk of contracting post-transplant diabetes mellitus, at least two of increased expression of HDAC5 protein; increased expression of HNF4A protein; decreased expression of NRF1 protein; decreased expression of PPARGC1 protein; and decreased expression of PPP3CA protein.