A system for managing delivery of genomic information for a cancer patient, the system comprising at least one processor operatively connected to a memory, the at least one processor being configured to: a) collect gene state data for a plurality of genes and store the gene state data in the memory; b) receive patient-specific pathology information relating to the cancer patient and storing the patient-specific pathology information in the memory; c) generate, from the gene state data and the patient-specific pathology information, a graph-based data structure comprising a plurality of tuples of information comprising: at least one tuple including a patient identifier connected to a particular disease through a diagnosis relation; at least one tuple including a disease connected to an alteration group through a disease alteration group association, DAGA wherein the AG defines a unique set of clinically relevant gene state data and wherein the DAGA associates the disease and the AG with one or more actionable items; d) traverse relationship associations in the graph-based data structure by following links between the gene state data, the patient-specific pathology information and the at least one DAGA to determine at least one inferred path through the graph-based data structure; characterized in that the at least one processor being further configured to e) generate, from the at least one inferred path, inferential matches to at least one actionable item available to the cancer patient based on an accumulated trust score for the at least one inferred path and the traversed relationship associations, wherein the at least one actionable item includes at least one of a recommendation for an enrollment of the cancer patient in a clinical trial and a recommendation for a therapy to be applied to the cancer patient. a) collect gene state data for a plurality of genes and store the gene state data in the memory; b) receive patient-specific pathology information relating to the cancer patient and storing the patient-specific pathology information in the memory; c) generate, from the gene state data and the patient-specific pathology information, a graph-based data structure comprising a plurality of tuples of information comprising: at least one tuple including a patient identifier connected to a particular disease through a diagnosis relation; at least one tuple including a disease connected to an alteration group through a disease alteration group association, DAGA wherein the AG defines a unique set of clinically relevant gene state data and wherein the DAGA associates the disease and the AG with one or more actionable items; at least one tuple including a patient identifier connected to a particular disease through a diagnosis relation; at least one tuple including a disease connected to an alteration group through a disease alteration group association, DAGA wherein the AG defines a unique set of clinically relevant gene state data and wherein the DAGA associates the disease and the AG with one or more actionable items; d) traverse relationship associations in the graph-based data structure by following links between the gene state data, the patient-specific pathology information and the at least one DAGA to determine at least one inferred path through the graph-based data structure;