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    Journals >NUCLEAR TECHNIQUES >Volume 46 >Issue 3 >Page 030101 > Article
    • NUCLEAR TECHNIQUES
    • Vol. 46, Issue 3, 030101 (2023)
    X-ray crystallography experimental data screening based on convolutional neural network algorithms
    Zi HUI1, Li YU2、3, Huan ZHOU4, Lin TANG1, and Jianhua HE1、*
    Author Affiliations
  • 1The Institute for Advanced Studies, Wuhan University, Wuhan 430072, China
  • 2Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
  • 4Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201204, China
    • show less
    DOI: 10.11889/j.0253-3219.2023.hjs.46.030101 Cite this Article
    Zi HUI, Li YU, Huan ZHOU, Lin TANG, Jianhua HE. X-ray crystallography experimental data screening based on convolutional neural network algorithms[J]. NUCLEAR TECHNIQUES, 2023, 46(3): 030101 Copy Citation Text show less
    References

    [1] Chapman H N, Fromme P, Barty A et al. Femtosecond X-ray protein nanocrystallography[J]. Nature, 470, 73-77(2011).

    [2] Emma P, Akre R, Arthur J et al. First lasing and operation of an ångstrom-wavelength free-electron laser[J]. Nature Photonics, 4, 641-647(2010).

    [3] Rossmann M G. Serial crystallography using synchrotron radiation[J]. IUCrJ, 1, 84-86(2014).

    [4] Stellato F, Oberthür D, Liang M N et al. Room-temperature macromolecular serial crystallography using synchrotron radiation[J]. IUCrJ, 1, 204-212(2014).

    [5] Nogly P, James D, Wang D J et al. Lipidic cubic phase serial millisecond crystallography using synchrotron radiation[J]. IUCrJ, 2, 168-176(2015).

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    [7] Ke T W, Brewster A S, Yu S X et al. A convolutional neural network-based screening tool for X-ray serial crystallography[J]. Journal of Synchrotron Radiation, 25, 655-670(2018).

    [8] Zimmermann J, Langbehn B, Cucini R et al. Deep neural networks for classifying complex features in diffraction images[J]. Physical Review E, 99, 063309(2019).

    [9] Howard A G, Zhu M, Chen B et al. MobileNets: efficient convolutional neural networks for mobile vision applications[EB/OL]. arXiv, 1704.04861(2017). https://arxiv.org/abs/1704.04861

    [10] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017).

    [11] Szegedy C, Vanhoucke V, Ioffe S et al. Rethinking the inception architecture for computer vision[C], 2818-2826(2016).

    [12] Szegedy C, Liu W, Jia Y Q et al. Going deeper with convolutions[C], 1-9(2015).

    [13] Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[EB/OL]. arXiv, 1409.1556(2014). https://arxiv.org/abs/1409.1556

    [14] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C], 770-778(2016).

    [15] Maia F R N C. The coherent X-ray imaging data bank[J]. Nature Methods, 9, 854-855(2012).

    [16] Goodfellow I, Bengio Y, Courville A[M]. Deep learning(2016).

    [17] JIAN Liqiong. Image enhancement algorithm based on two-dimensional histogram equalization[J]. China Computer & Communication, 2015, 49-54.

    [18] Reid C R. From functional architecture to functional connectomics[J]. Neuron, 75, 209-217(2012).

    [19] LeCun Y, Boser B, Denker J S et al. Backpropagation applied to handwritten zip code recognition[J]. Neural Computation, 1, 541-551(1989).

    [20] Abadi M, Agarwal A, Barham P et al. TensorFlow: large-scale machine learning on heterogeneous distributed systems[ED/OL]. https://arxiv.org/abs/1603.04467

    [21] Der Maaten L V, Hinton G E. Visualizing data using t-SNE[J]. Journal of Machine Learning Research, 9, 2579-2605(2008).

    [22] Wang Q S, Zhang K H, Cui Y et al. Upgrade of macromolecular crystallography beamline BL17U1 at SSRF[J]. Nuclear Science and Techniques, 29, 68(2018).

    [23] Zhang W Z, Tang J C, Wang S S et al. The protein complex crystallography beamline (BL19U1) at the Shanghai Synchrotron Radiation Facility[J]. Nuclear Science and Techniques, 30, 170(2019).

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    Zi HUI, Li YU, Huan ZHOU, Lin TANG, Jianhua HE. X-ray crystallography experimental data screening based on convolutional neural network algorithms[J]. NUCLEAR TECHNIQUES, 2023, 46(3): 030101
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