徐莹莹

姓名：徐莹莹

职称：副教授

联系邮箱：yyxu@smu.edu.cn 

个人主页：https://yingying-xu.github.io/ 

学习经历（学士、硕士、博士）：

2011.09-2017.06 上海交通大学，模式识别与智能系统，博士

2015.09-2016.09 美国卡内基梅隆大学，计算生物学，联合培养博士生

工作经历：

2017.07至今 南方医科大学，副教授

研究方向：

生物图像信息学与模式识别

主要科研课题：

1、广东省自然科学基金面上项目，2022A15150 11436，基于深度学习的蛋白质荧光图像亚细胞位置分布的定量研究及应用，2022.01-2024.12，10万，主持

2、国家自然科学基金青年项目，61803196，基于多尺度空间建模的蛋白质亚细胞定位预测及应用研究，2019.01-2021.12，27万，主持，已结题

3、广东省自然科学基金，2018030310282，免疫组化显微图像中蛋白质的复杂亚细胞位置模式的定量分析及应用研究，2018.05-2021.04，10万，主持，已结题

代表性论文：

（1）Xi-Liang Zhu, Lin-Xia Bao, Min-Qi Xue, and Ying-Ying Xu*. Automatic recognition of protein subcellular location patterns in single cells from immunofluorescence images based on deep learning. Briefings in Bioinformatics, 2022, 24(1):bbac609. (SCI, IF=13.994)

（2）Zhen-Zhen Xue, Cheng Li, Zhuo-Ming Luo, Shan-Shan Wang, and Ying-Ying Xu*. Automated classification of protein expression levels in immunohistochemistry images to improve the detection of cancer biomarkers. BMC Bioinformatics, 2022, 23:470. (SCI, IF=3.327)

（3）Jin-Xian Hu, Yang Yang, Ying-Ying Xu* , and Hong-Bin Shen*. GraphLoc: a graph neural network model for predicting protein subcellular localization from immunohistochemistry images. Bioinformatics, 2022, 38(21):4941–4948. (SCI, IF=6.931)

（4）Xi-Liang Zhu, Hong-Bin Shen, Haitao Sun, Li-Xia Duan* , and Ying-Ying Xu*. Improving segmentation and classification of renal tumors in small sample 3D CT images using transfer learning with convolutional neural networks. International Journal of Computer Assisted Radiology and Surgery, 2022, 17(7):1303-1311. (SCI, IF=3.421)

（5）Ge Wang, Min-Qi Xue, Hong-Bin Shen*, and Ying-Ying Xu*. Learning protein subcellular localization multi-view patterns from heterogeneous data of imaging, sequence and networks. Briefings in Bioinformatics, 2022, 23(2):bbab539. (SCI, IF=11.622)

（6）Min-Qi Xue, Xi-Liang Zhu, Ge Wang, and Ying-Ying Xu*. DULoc: quantitatively unmixing protein subcellular location patterns in immunofluorescence images based on deep learning features. Bioinformatics, 2022, 38(3):827–833. (SCI, IF=6.937)

（7）Jin-Xian Hu, Yang Yang, Ying-Ying Xu* , and Hong-Bin Shen*. Incorporating label correlations into deep neural networks to classify protein subcellular location patterns in immunohistochemistry images. PROTEINS: Structure, Function, and Bioinformatics, 2022, 90(2):493-503. (SCI, IF=3.756)

（8）Ge Wang, Yu-Jia Zhai, Zhen-Zhen Xue, and Ying-Ying Xu*. Improving protein subcellular location classification by incorporating three-dimensional structure information. Biomolecules, 2021, 11(11):1607. (SCI, IF=4.879)

（9）Ying-Ying Xu, Hang Zhou, Robert F. Murphy, and Hong-Bin Shen*. Consistency and variation of protein subcellular location annotations. PROTEINS: Structure, Function, and Bioinformatics, 2021, 89(2):242-250. (SCI, IF=2.828)

（10）Zhen-Zhen Xue, Yanxia Wu, Qing-Zu Gao, Liang Zhao, Ying-Ying Xu*. Automated classification of protein subcellular localization in immunohistochemistry images to reveal biomarkers in colon cancer, BMC Bioinformatics, 2020, 21:398. (SCI, IF=3.242)

（11）Ying-Ying Xu, Hong-Bin Shen*, Robert F. Murphy*, Learning complex subcellular distribution patterns of proteins via analysis of immunohistochemistry images, Bioinformatics, 2020, 36(6): 1908-1914. (SCI, IF=5.61)

（12）Ying-Ying Xu, Li-Xiu Yao, Hong-Bin Shen*, Bioimage-based protein subcellular location prediction: a comprehensive review, Frontiers of Computer Science, 2018, 12(1): 26-39. (SCI, IF=1.275)

（13）Wei Shao, Ming-Xia Liu, Ying-Ying Xu, Hong-Bin Shen, Dao-Qiang Zhang, An organelle correlation-guided feature selection approach for classifying multi-label subcellular bioimages, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018, 15(3):828-838. (SCI, IF=3.015)

（14）Ying-Ying Xu, Fan Yang, Hong-Bin Shen*, Incorporating organelle correlations into semi-supervised learning for protein subcellular localization prediction, Bioinformatics, 2016, 32:2184-2192. (SCI, IF=5.61)

（15）Xi Yin, Ying-Ying Xu, Hong-Bin Shen*, Enhancing the prediction of transmembrane beta-barrel segments with chain learning and feature sparse representation, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2016, 13(6):1016-1026. (SCI, IF=3.015)

（16）Ying-Ying Xu, Fan Yang, Yang Zhang, Hong-Bin Shen*, Bioimaging based detection of mislocalized proteins in human cancers by semi-supervised learning, Bioinformatics, 2015, 31:1111-1119. (SCI, IF=5.61)

（17）Fan Yang, Ying-Ying Xu, Shi-Tong Wang, Hong-Bin Shen*, Image-based classification of protein subcellular location patterns in human reproductive tissue by ensemble learning global and local features, Neurocomputing, 2014, 131:113-123. (SCI, IF=4.438)

（18）Ying-Ying Xu, Fan Yang, Yang Zhang*, Hong-Bin Shen*, An image-based multi-label human protein subcellular localization predictor (iLocator) reveals protein mislocalizations in cancer tissues, Bioinformatics, 2013, 29:2032-2040. (SCI, IF=5.61)