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Our research demonstrates the feasibility of Integer Linear Programming (ILP) to structure a mid-density genotyping panel from heterogenous source knowledge. In the absence of readily available high-self-assurance targets, and provided the design conditions and aims can be expressed as linear equations, ILP is more explainable than machine learning