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A molecular computing model for maximal clique problem using circular DNA length growth

机译:使用环状DNA长度增长的最大集团问题的分子计算模型

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A novel DNA computing model based on circular DNA length growth (CDLG) is developed to solve a maximal clique problem (MCP) with n-vertices. The time complexity of biological operations required is O(n+m) (m is the number of edges of the complementary graph), and the space complexity is O(n+m). The main feature of this model is using circular single-stranded DNA (c-ssDNA) to implement the computation on the nano-scale. By the CDLG method, the target DNA molecules will grow in length just when they satisfy the conditions. To verify the algorithm, a small paradigm is calculated by the nano-scale DNA computing model. The computing achievement by circular DNA demonstrates the potential ability of DNA computing to solve NP-complete problems.
机译:开发了一种基于环状DNA长度增长(CDLG)的新型DNA计算模型,以解决具有n个顶点的最大集团问题(MCP)。所需生物操作的时间复杂度为O(n + m)(m是互补图的边数),而空间复杂度为O(n + m)。该模型的主要特征是使用环状单链DNA(c-ssDNA)进行纳米级的计算。通过CDLG方法,目标DNA分子只要满足条件,其长度就会增加。为了验证该算法,纳米尺度DNA计算模型计算出一个小的范例。圆环DNA的计算成就证明了DNA计算解决NP完全问题的潜在能力。

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