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| 1 | Detecting protein complexes from DPINs by density based clustering with Pigeon-Inspired Optimization Algorithm显示文摘Detecting protein complexes is crucial to understand principles of cellular organization. Plenty evidences have indicated that sub-graphs with high density in protein-protein interaction(PPI) network, especially dynamic PPI network(DPIN), usually correspond to protein complexes. As a well-known density-based clustering algorithm, Density-Based Spatial Clustering of Applications with Noise(DBSCAN) has been used in many areas due to its simplicity and the ability to detect clusters of different sizes and shapes. However, one of its limitations is that the performance of DBSCAN depends on two specified parameters ε and Min Pts, where εrepresents the maximum radius of a neighborhood from an observing point while Min Pts means the minimum number of data points contained in such a neighborhood. In this article, we develop a new method named as P-DBSCAN to detect protein complexes in DPIN by using Pigeon-Inspired Optimization(PIO) Algorithm to optimize the parameters ε and Min Pts in DBSCAN. The experiments on DIP and MIPS datasets show that P-DBSCAN outperforms the state-of-the-art methods for protein complex detection in terms of several criteria such as precision, recall and f-measure. | Xiujuan LEI Yulian DING Fang-Xiang WU | 2016 | Science China(Information Sciences)2016，59，7： | 9 |
| 2 | 用并行蚁群系统解决带假结RNA二级结构预测显示文摘RNA是生物遗传信息的中间载体,在基因编码、解码、调控和表达等方面具有重要作用.RNA二级结构预测是理解RNA生化功能的主要途径.假结是最广泛的RNA结构单元.带假结的RNA二级结构预测难度大,已被证明是一个NP完全问题,至今未找到该问题有效的多项式算法.本文将带假结RNA二级结构预测建模为一个多目标优化问题,在Prob Knot方法的基础上,设计两种基于碱基配对概率的改进方案,并采用最大最小蚁群方法优化原本的贪婪法.此外,引入并行的机制和共享信息素矩阵的方式,提出一种并行的带假结RNA二级结构预测方法.选取常用的RNA STRAND数据集,与常见的带假结RNA二级结构预测方法作比较.实验结果表明,本文的方法可以有效地提高带假结RNA二级结构预测的精度. | 蔡磊鑫 顾倜 王帅 吕强 | 2017 | 小型微型计算机系统2017，38，10： | 1 |
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