1. Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G.S., Davis, A., Dean, J., Devin, M., Ghemawat, S., Goodfellow, I., Harp, A., Irving, G., Isard, M., Jia, Y., Jozefowicz, R., Kaiser, L., Kudlur, M., Levenberg, J., Mané, D., Monga, R., Moore, S., Murray, D., Olah, C., Schuster, M., Shlens, J., Steiner, B., Sutskever, I., Talwar, K., Tucker, P., Vanhoucke, V., Vasudevan, V., Viégas, F., Vinyals, O., Warden, P., Wattenberg, M., Wicke, M., Yu, Y., Zheng, X., 2015. TensorFlow: Large-scale machine learning on heterogeneous systems, software available from tensorflow.org. URL http://tensorflow.org/.
2. A binary segmentation approach for boxing ribosome particles in cryo EM micrographs;Adiga;J. Struct. Biol.,2004
3. Experimental evaluation of support vector machine-based and correlation-based approaches to automatic particle selection;Arbelez;J. Struct. Biol.,2011
4. How cryo-EM is revolutionizing structural biology;Bai;Trends Biochem. Sci.,2015
5. Structure of β-galactosidase at 3.2-Å resolution obtained by cryo-electron microscopy;Bartesaghi;Proc. Nat. Acad. Sci.,2014