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随着新一代测序技术的发展,一些新的全基因组组装算法应运而生,特别是针对第三代高通量测序仪产生的海量短序列的组装软件被不断开发出来,这些组装软件渐渐走向市场。但是,由于这些组装软件的适用性和其性能的差别,选择一款性能优良的组装工具或者开发并行高吞吐的组装工具成为了当前面临的一大难题。本文选取基于 De Bruijn 图算法开发的 4 款 De Novo 组装的软件(Velvet、SOAPdenovo、IDBA、ABySS)对 4 种物种的基因组的模拟数据进行测试,并从软件的算法、组装性能和组装质量 3 个方面分析这 4 个软件的性能,同时根据其算法特点推断影响这些软件性能的关键因素,并给出软件的使用建议以及开发并行序列组装工具来组装超大规模的基因数据应该注意的问题。  相似文献   
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Power saving is one of the key issues in Mobile Ad-Hoc Networks(MANETs).It can be realized in Medium Access Control(MAC) layer and network layer.However,previous attentions were mainly paid to MAC layer or network layer with the aim of improving the channel utilization by adopting variable-range transmission power control.In this paper we focus on the power saving in both MAC layer and network layer,and propose a Power Adjusting Algorithm(PAA).In the presence of host’s mobility,PAA is designed to conserve energy by adjusting the transmission power to maintain the route’s connectivity and restarting the route discovery periodically to find a new route with better energy efficiency dynamically.After analyzing the operations of PAA,we find that the length of route discovery restarting period is a critical argument which will affect power saving,and an energy consumption model is abstracted to find the optimal value of the restarting period by analyzing the energy consumption of this algorithm.PAA can handle the mobility of MANET by adjusting the transmission power and in the meantime save energy by restarting route discovery periodically to balance the energy consumption on route discovery and packet delivering.Simulation results show that,PAA saves nearly 40% energy compared with Dynamic Source Routing protocol when the maximum speed of mobile hosts is larger than 8m/s.  相似文献   
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