目的采用生物信息学方法分析结核分枝杆菌的Rv0824c基因及其编码的DesA1蛋白结构和功能。方法自NCBI网站获取Rv0824c基因及DesA1蛋白的基本信息;使用Protparam、ProtScale和ProtCompB预测DesA1蛋白的理化性质、亲疏水性和亚细胞定位;使...目的采用生物信息学方法分析结核分枝杆菌的Rv0824c基因及其编码的DesA1蛋白结构和功能。方法自NCBI网站获取Rv0824c基因及DesA1蛋白的基本信息;使用Protparam、ProtScale和ProtCompB预测DesA1蛋白的理化性质、亲疏水性和亚细胞定位;使用SignalP Server v.4.0、TMHMM Server v.2.0、NetNGlyc 1.0 server和NetPhos Server v.3.1预测DesA1蛋白的信号肽、跨膜结构、糖基化及磷酸化位点;使用SOPMA和SWISS MODEL预测DesA1蛋白的二级结构并构建该蛋白的三级结构模型;使用ABCpred和SYFPEITHI预测DesA1蛋白的抗原表位;使用MEGA软件构建系统发育树;使用STRING数据库预测DesA1的相互作用蛋白及相关功能。结果Rv0824c基因全长1017 bp,编码的DesA1蛋白氨基酸数为338,分子式为C_(1723)H_(2694)N_(490)O_(503)S_(14),等电点(pI)为6.21,平均亲水性系数为-0.461,预测其为亲水性蛋白,亚细胞可能定位于细胞壁或细胞质。DesA1蛋白无跨膜结构、信号肽和糖基化位点,有20个磷酸化位点;二级结构包含66.86%的α-螺旋(Hh),2.96%的β-折叠(Ee),5.03%的β-转角(Tt),25.15%无规则卷曲(Cc)。DesA1蛋白含有34个B细胞抗原,15个T细胞优势抗原。系统进化树显示其与卡内特分枝杆菌(Mycobacterium canettii)DesA1蛋白具有最大同源性;其互作蛋白为Fas、DesA2、DesA3、Ppdk、NrdZ、NrdE、NrdL、Pks13、Dus及Rv3230c蛋白,主要参与脂质代谢过程。结论生物信息学方法预测DesA1为亲水性蛋白,具有多个潜在的B、T细胞抗原表位,能够磷酸化并与多种蛋白相互作用,有可能成为研发结核病疫苗的候选蛋白。展开更多
对于带未知模型参数和噪声方差的多传感器系统,基于分量按标量加权最优融合准则,提出了自校正解耦融合Kalman滤波器,并应用动态误差系统分析(Dynamic error system analysis,DESA)方法证明了它的收敛性.作为在信号处理中的应用,对带有...对于带未知模型参数和噪声方差的多传感器系统,基于分量按标量加权最优融合准则,提出了自校正解耦融合Kalman滤波器,并应用动态误差系统分析(Dynamic error system analysis,DESA)方法证明了它的收敛性.作为在信号处理中的应用,对带有色和白色观测噪声的多传感器多维自回归(Autoregressive,AR)信号,分别提出了AR信号模型参数估计的多维和多重偏差补偿递推最小二乘(Bias compensated recursive least-squares,BCRLS)算法,证明了两种算法的等价性,并且用DESA方法证明了它们的收敛性.在此基础上提出了AR信号的自校正融合Kalman滤波器,它具有渐近最优性.仿真例子说明了其有效性.展开更多
As the proportion of renewable energy sources continues to increase,the local damping contributions of sources in power system decrease,posing a challenge to the power system stability.Therefore,online tracking of the...As the proportion of renewable energy sources continues to increase,the local damping contributions of sources in power system decrease,posing a challenge to the power system stability.Therefore,online tracking of the damping contributions of each source is crucial for the prevention of low-frequency oscillations.This paper proposes an online tracking method of local damping under ambient data.The proposed method is based on dissipation energy spectrum analysis(DESA)and the energy dissipation factor(EDF).First,the feasibility of using frequency-domain analysis for the dissipation energy of generator is analyzed.The frequency spectral function of dissipation energy of generator is then derived by integrating with Parseval’s theorem,and the EDF is defined.Second,the generator energy dissipation factor(GEDF)for the dominant oscillation mode frequency is established.The modal information of the dominant oscillation in the power system is obtained through DESA.The relationship between the frequency spectral function and eigenvalues is also established.Finally,an online tracking method of local damping is proposed based on DESA and GEDF.The effectiveness of the proposed method is validated through simulations on a four-machine 11-bus power system and an actual power system in Northwest China.展开更多
文摘目的采用生物信息学方法分析结核分枝杆菌的Rv0824c基因及其编码的DesA1蛋白结构和功能。方法自NCBI网站获取Rv0824c基因及DesA1蛋白的基本信息;使用Protparam、ProtScale和ProtCompB预测DesA1蛋白的理化性质、亲疏水性和亚细胞定位;使用SignalP Server v.4.0、TMHMM Server v.2.0、NetNGlyc 1.0 server和NetPhos Server v.3.1预测DesA1蛋白的信号肽、跨膜结构、糖基化及磷酸化位点;使用SOPMA和SWISS MODEL预测DesA1蛋白的二级结构并构建该蛋白的三级结构模型;使用ABCpred和SYFPEITHI预测DesA1蛋白的抗原表位;使用MEGA软件构建系统发育树;使用STRING数据库预测DesA1的相互作用蛋白及相关功能。结果Rv0824c基因全长1017 bp,编码的DesA1蛋白氨基酸数为338,分子式为C_(1723)H_(2694)N_(490)O_(503)S_(14),等电点(pI)为6.21,平均亲水性系数为-0.461,预测其为亲水性蛋白,亚细胞可能定位于细胞壁或细胞质。DesA1蛋白无跨膜结构、信号肽和糖基化位点,有20个磷酸化位点;二级结构包含66.86%的α-螺旋(Hh),2.96%的β-折叠(Ee),5.03%的β-转角(Tt),25.15%无规则卷曲(Cc)。DesA1蛋白含有34个B细胞抗原,15个T细胞优势抗原。系统进化树显示其与卡内特分枝杆菌(Mycobacterium canettii)DesA1蛋白具有最大同源性;其互作蛋白为Fas、DesA2、DesA3、Ppdk、NrdZ、NrdE、NrdL、Pks13、Dus及Rv3230c蛋白,主要参与脂质代谢过程。结论生物信息学方法预测DesA1为亲水性蛋白,具有多个潜在的B、T细胞抗原表位,能够磷酸化并与多种蛋白相互作用,有可能成为研发结核病疫苗的候选蛋白。
基金supported by National Key Research and Development Program of China(No.2021YFB2400800).
文摘As the proportion of renewable energy sources continues to increase,the local damping contributions of sources in power system decrease,posing a challenge to the power system stability.Therefore,online tracking of the damping contributions of each source is crucial for the prevention of low-frequency oscillations.This paper proposes an online tracking method of local damping under ambient data.The proposed method is based on dissipation energy spectrum analysis(DESA)and the energy dissipation factor(EDF).First,the feasibility of using frequency-domain analysis for the dissipation energy of generator is analyzed.The frequency spectral function of dissipation energy of generator is then derived by integrating with Parseval’s theorem,and the EDF is defined.Second,the generator energy dissipation factor(GEDF)for the dominant oscillation mode frequency is established.The modal information of the dominant oscillation in the power system is obtained through DESA.The relationship between the frequency spectral function and eigenvalues is also established.Finally,an online tracking method of local damping is proposed based on DESA and GEDF.The effectiveness of the proposed method is validated through simulations on a four-machine 11-bus power system and an actual power system in Northwest China.
