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Noisy Nonlinear Gene Regulatory Networks Analysis Using Ensemble Kalman Filter Based Particle Filter without a Model

机译：嘈杂的非线性基因监管网络使用基于集合Kalman滤波器的粒子滤波器而没有模型

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Haixin Wang; Dawit Aberra;
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1. Inference of Noisy Nonlinear Differential Equation Models for Gene Regulatory Networks Using Genetic Programming and Kalman Filtering [J] . Qian L., Wang H., Dougherty E. R. IEEE Transactions on Signal Processing . 2008,第7期

机译：基于遗传规划和卡尔曼滤波的基因调控网络噪声非线性微分方程模型的推论
2. An extended Kalman filtering approach to modeling nonlinear dynamic gene regulatory networks via short gene expression time series [J] . Jason Moore Computing reviews . 2010,第6期

机译：通过短基因表达时间序列对非线性动态基因调控网络建模的扩展卡尔曼滤波方法
3. An Extended Kalman Filtering Approach to Modeling Nonlinear Dynamic Gene Regulatory Networks via Short Gene Expression Time Series [J] . Zidong Wang, Xiaohui Liu, Yurong Liu, Computational Biology and Bioinformatics, IEEE/ACM Transactions on . 2009,第3期

机译：基于短基因表达时间序列的非线性动态基因调控网络建模的扩展卡尔曼滤波方法
4. Modeling Genetic Regulatory Networks by Sigmoidal Functions: A Joint Genetic Algorithm and Kalman Filtering Approach [C] . Wang Haixin, Qian Lijun, Dougherty Edward, International Conference on Natural Computation . 2007

机译：乙型函数建模遗传监管网络：一种联合遗传算法和卡尔曼滤波方法
5. Nonlinear estimation and modeling of noisy time series by dual Kalman filtering methods. [D] . Nelson, Alex Tremain. 2000

机译：用双重卡尔曼滤波方法对噪声时间序列进行非线性估计和建模。
6. A Kalman-Filter Based Approach to Identification of Time-Varying Gene Regulatory Networks [O] . Jie Xiong, Tong Zhou -1

机译：基于卡尔曼滤波的时变基因调控网络识别方法
7. Inference of noisy nonlinear differential equation models for gene regulatory networks using genetic programming and kalman filtering [O] . Lijun Qian, Senior Member, Haixin Wang, 2008

机译：基于遗传规划和卡尔曼滤波的基因调控网络噪声非线性微分方程模型的推断
8. Representer Method, the Ensemble Kalman Filter and the Ensemble Kalman Smoother: A Comparison Study Using a Nonlinear Reduced Gravity Ocean Model [R] . Ngodock, H. E. , Jacobs, G. A. , Chen, M. 2006

机译：代表法，集合卡尔曼滤波器和集合卡尔曼平滑器：非线性减少重力海洋模型的比较研究

Noisy Nonlinear Gene Regulatory Networks Analysis Using Ensemble Kalman Filter Based Particle Filter without a Model

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