生物网络是系统生物学研究的重要内容。本文介绍了多种常用复杂生物网络可视化系统,针对Cytoscape系统在可视化的建模过程以及在建模过程中使用到的布局算法进行对比研究,并利用Cytoscape系统中丰富的插件对复杂网络数据进行分析,包括...生物网络是系统生物学研究的重要内容。本文介绍了多种常用复杂生物网络可视化系统,针对Cytoscape系统在可视化的建模过程以及在建模过程中使用到的布局算法进行对比研究,并利用Cytoscape系统中丰富的插件对复杂网络数据进行分析,包括对数据进行网络分析和更改、使用BINGO插件进行基因注释、使用AGILENT LITERATURE SEARCH(ALS)插件搜索基因相互作用文献等。展开更多
Inertial navigation system/visual navigation system(INS/VNS) integrated navigation is a commonly used autonomous navigation method for planetary rovers. Since visual measurements are related to the previous and curren...Inertial navigation system/visual navigation system(INS/VNS) integrated navigation is a commonly used autonomous navigation method for planetary rovers. Since visual measurements are related to the previous and current state vectors(position and attitude) of planetary rovers, the performance of the Kalman filter(KF) will be challenged by the time-correlation problem. A state augmentation method, which augments the previous state value to the state vector, is commonly used when dealing with this problem. However, the augmenting of state dimensions will result in an increase in computation load. In this paper, a state dimension reduced INS/VNS integrated navigation method based on coordinates of feature points is presented that utilizes the information obtained through INS/VNS integrated navigation at a previous moment to overcome the time relevance problem and reduce the dimensions of the state vector. Equations of extended Kalman filter(EKF) are used to demonstrate the equivalence of calculated results between the proposed method and traditional state augmented methods. Results of simulation and experimentation indicate that this method has less computational load but similar accuracy when compared with traditional methods.展开更多
文摘生物网络是系统生物学研究的重要内容。本文介绍了多种常用复杂生物网络可视化系统,针对Cytoscape系统在可视化的建模过程以及在建模过程中使用到的布局算法进行对比研究,并利用Cytoscape系统中丰富的插件对复杂网络数据进行分析,包括对数据进行网络分析和更改、使用BINGO插件进行基因注释、使用AGILENT LITERATURE SEARCH(ALS)插件搜索基因相互作用文献等。
基金supported by the National Natural Science Foundation of China (Nos. 61233005 and 61503013)the National Basic Research Program of China (No. 2014CB744202)+2 种基金Beijing Youth Talent ProgramFundamental Science on Novel Inertial Instrument & Navigation System Technology LaboratoryProgram for Changjiang Scholars and Innovative Research Team in University (IRT1203) for their valuable comments
文摘Inertial navigation system/visual navigation system(INS/VNS) integrated navigation is a commonly used autonomous navigation method for planetary rovers. Since visual measurements are related to the previous and current state vectors(position and attitude) of planetary rovers, the performance of the Kalman filter(KF) will be challenged by the time-correlation problem. A state augmentation method, which augments the previous state value to the state vector, is commonly used when dealing with this problem. However, the augmenting of state dimensions will result in an increase in computation load. In this paper, a state dimension reduced INS/VNS integrated navigation method based on coordinates of feature points is presented that utilizes the information obtained through INS/VNS integrated navigation at a previous moment to overcome the time relevance problem and reduce the dimensions of the state vector. Equations of extended Kalman filter(EKF) are used to demonstrate the equivalence of calculated results between the proposed method and traditional state augmented methods. Results of simulation and experimentation indicate that this method has less computational load but similar accuracy when compared with traditional methods.
