Fast, Adaptive Expectation-Maximization Alignment for Cryo-EM

被引:0
|
作者
Tagare, Hemant D. [1 ,2 ]
Sigworth, Frederick [2 ,3 ]
Barthel, Andrew [2 ]
机构
[1] Yale Univ, Dept Diag Radiol, New Haven, CT 06520 USA
[2] Yale Univ, Dept Biomed Engn, New Haven, CT 06520 USA
[3] Yale Univ, Dept Physiol, New Haven, CT 06520 USA
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Cryo-EM is a method for reconstructing 3D structure of proteins without crystallization. The Expectation-Maximization (EM) algorithm is used in the alignment step of Cryo-EM reconstructions. The EM step is often a serious computational bottleneck for 3D reconstructions. This paper proposes a computationally adaptive version of the EM algorithm that speeds up the algorithm by a factor of 20 - 30. Experiments with noisy real-world data are included to show that the algorithm achieves this speedup without any significant loss of accuracy. Such speed ups are significant, allowing the reconstruction to converge in cpu-days rather than cpu-months.
引用
收藏
页码:855 / 862
页数:8
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