Abstract
Existing sample preparation algorithms are either based on NP-style problem formulations, e.g., using integer linear programming (ILP), which runs very slowly, or based on heuristic algorithms, which cannot obtain optimal solutions regarding different objectives. This paper proposes the first online sample preparation algorithm based on the lookup table method, named LUTOSAP. LUTOSAP enables fast query response for online sample preparation requirements with the solution where the weighted sum of sample consumption, buffer consumption, and the number of mix-split operations is optimized. Experimental results show that LUTOSAP obtains optimal sample preparation solutions in microseconds within the accuracy tolerance of $0.2\%$ for both single and double concentration values, which is orders of magnitude faster than existing algorithms. For multiple concentration values, the multiple-target sample preparation algorithm in LUTOSAP obtains near-optimal solution based on the constructed lookup table in microseconds, which well meets the critical fast-response requirements in online sample preparation.
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