|On the cover: On the cover: Nourished by the gigantic data and empowered by increasing computing facilities, Artificial Intelligence (AI) is setting us free from many burdensome routines. With AI muscles, we have become faster and smarter than ever. AI is reshaping the future of industries and our lives, enabling paradigm shifts in many disciplines of science and even paving the road to the metaverse. But scientists are still facing endless choices to navigate their innovation processes as previously. Meanwhile, collaborations are urgently needed amongst researchers from multidisciplinary studies. So we do hope the shared values of truth, righteousness, and peace can be cherished deeply to make our blue planet a better place for the whole ecosystem.|
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|Position: Home > issue > November 28, 2021 Volume 2, Issue 4|
|Determining structures in a native environment using single-particle cryoelectron microscopy images|
|Category: Report Download: PDF Figure Endnote|
|Author: Jing Cheng, Bufan Li, Long Si, Xinzheng Zhang|
Cryo-electron tomography is a powerful tool for structure determination in the native environment. However, this method requires the acquisition of tilt series, which is time-consuming and severely slows structure determination. By treating the densities of non-target protein as non-Gaussian noise, we developed a new target function that greatly improves the efficiency of recognizing the target protein in a single cryo-electron microscopy image. Moreover, we developed a sorting function that effectively eliminates the model dependence and improved the resolution during the subsequent structure refinement procedure.
Cheng J., Li B., Si L., et al. (2021). Determining structures in a native environment using single-particle cryo-electron microscopy images. The Innovation. 2(4),100166.