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DeepPicker specifications


Unique identifier OMICS_19137
Name DeepPicker
Software type Framework/Library
Interface Command line interface
Restrictions to use None
Programming languages Python
Computer skills Advanced
Stability Stable
Maintained Yes




No version available


  • person_outline Jianyang Zeng
  • person_outline Xueming Li

Publication for DeepPicker

DeepPicker citations


Opportunities and obstacles for deep learning in biology and medicine

PMCID: 5938574
PMID: 29618526
DOI: 10.1098/rsif.2017.0387

[…] approaches are semi-supervised; a user will select several particles manually, and these selections will be used to train a classifier [,]. now cnns are being used to select particles in tools like deeppicker [] and deepem []. in addition to addressing shortcomings from manual selection, such as selection bias and poor discrimination of low-contrast images, these approaches also provide a means […]


Structure of the human activated spliceosome in three conformational states

Cell Res
PMCID: 5835773
PMID: 29360106
DOI: 10.1038/cr.2018.14

[…] consistent with the rationale, the spliceosomes derived from sample ii are exclusively the early bact complexes., for data set i, 1 464 033 particles were auto-picked using the deep-learning program deeppicker. the convolutional neural network model for particle picking was trained using the previous data set of the ils complex from s. pombe. a guided multi-reference classification procedure […]

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DeepPicker institution(s)
School of Life Sciences, Tsinghua University, Beijing, China; Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China; School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China; Beijing Advanced Innovation Center for Structure Biology, Tsinghua University, Beijing, China; Tsinghua-Peking Joint Center for Life Sciences, Tsinghua University, Beijing, China
DeepPicker funding source(s)
Supported by the National Basic Research Program of China (Grant 2011CBA00300, 2011CBA00301), the National Natural Science Foundation of China (Grants 61033001, 61361136003 and 61472205, 31570730, and 61571202), China Youth 1000-Talent Program by the State Council of China, Beijing Advanced Innovation Center for Structural Biology, and Tsinghua-Peking Joint Center for Life Sciences.

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