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Searching Method of Structural Similar Subnets in Protein-protein Interaction Networks Based on Quantum Walks

机译：基于量子散步的蛋白质 - 蛋白质相互作用网络中结构相似子网的搜索方法

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Comparing and investigation into different protein-protein interaction networks (PPI networks) is significant for discovering new biological function and comprehending the evolution of the protein-protein interactions. Because general PPI networks are large in scale, existing classical computation algorithms of solving alignment and search in PPI networks possess too high time complexity. The time complexity is so high that it is impossible for the algorithm to align the whole network simultaneously. An effective quantum algorithm, Quantum-walks Algorithm for PPI-network Similar Subnets Searching (QPSS), is introduced to improve the situation mentioned above based on the continuous-time quantum-walks model in quantum computation. The process in detail of the QPSS algorithm is demonstrated. Moreover, we discuss the performance evaluation of this algorithm. After the time complexity of QPSS algorithm compares with its classical counterpart, it has been proved that the QMSM obtains a nearly quadratic speed-up.
机译：不同蛋白质 - 蛋白质相互作用网络（PPI网络）的比较和研究对于发现新的生物学功能并理解蛋白质 - 蛋白质相互作用的演变是显着的。因为一般PPI网络的规模大，所以在PPI网络中解决对齐和搜索的现有经典计算算法具有太高的时间复杂度。时间复杂性如此之高，算法不可能同时对齐整个网络。引入了一种有效量子算法，量子播放算法，用于PPI网络类似的子网搜索（QPS），以改善基于量子计算中的连续时间量子播放模型的上述情况。对QPSS算法详细的过程进行了说明。此外，我们讨论了该算法的性能评估。在QPSS算法的时间复杂性与其经典对应物比较之后，已经证明QMSM获得了几乎二次加速。

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