Papers and Pre-prints

See here for the full list. See here for corresponding citations in latex bib format.

Cryo-ET analysis

  1. Bandyopadhyay H, Deng Z, Ding L, Liu S, Uddin M, Zeng X, Xu M. Cryo-shift: Reducing domain shift in cryo-electron subtomograms with unsupervised domaina daptation and randomization. Bioinformatics. doi:10.1093/bioinformatics/btab794, arXiv:2111.09114
  2. Zeng X, Howe G, Xu M. End-to-end robust joint unsupervised image alignment and clustering. International Conference on Computer Vision (ICCV 2021)
  3. Zhu X, Chen J, Zeng X, Liang J, Li C, Liu S, Behpour S, Xu M. Weakly Supervised 3D Semantic Segmentation Using Cross-Image Consensus and Inter-Voxel Affinity Relations. International Conference on Computer Vision (ICCV 2021)
  4. Zeng Y, Howe G, Yi K, Zeng X, Zhang J, Chang Y, Xu M. Unsupervised Domain Alignment based Open Set Structural Recognition of Macromolecules Captured by Cryo-Electron Tomography. 2021 IEEE International Conference on Image Processing (ICIP)
  5. Zeng X, Kahng A, Xue L, Mahamid J, Chang Y, Xu M. DISCA: high-throughput cryo-ET structural pattern mining by deep unsupervised clustering. bioRxiv. doi:10.1101/2021.05.16.444381
  6. Gao S, Han R, Zeng X, Xu M, Zhang F. Macromolecules Structural Classification with a 3D Dilated Dense Network in Cryo-electron Tomography. IEEE/ACM Transactions on Computational Biology and Bioinformatics. doi:10.1109/TCBB.2021.3065986
  7. Du X, Wang H, Zhu Z, Zeng X, Chang Y, Zhang J, Xu M. Active learning to classify macromolecular structures in situ for less supervision in cryo-electron tomography. Bioinformatics. doi:10.1093/bioinformatics/btab123 arXiv:2102.12040
  8. Zhou B, Yu H, Zeng X, Yang X, Zhang J, Xu M. One-shot Learning with Attention-guided Segmentation in Cryo-Electron Tomography. Frontiers in Molecular Biosciences. doi:10.3389/fmolb.2020.613347
  9. Liu S, Ma Y, Ban X, Zeng X, Nallapareddy V, Chaudhari A, Xu M. Efficient Cryo-Electron Tomogram Simulation of Macromolecular Crowding with Application to SARS-CoV-2. BIBM 2020
  10. Li R, Yu L, Zhou B, Zeng X, Wang Z, Yang X, Zhang J, Gao X, Jang R, Xu M. Few-shot learning for classification of novel macromolecular structures in cryo-electron tomograms. PLOS Computational Biology. doi:10.1371/journal.pcbi.1008227
  11. Yu L, Li R, Zeng X, Wang H, Jin J, Yang G, Jiang R, Xu M. Few Shot Domain Adaptation for in situ Macromolecule Structural Classification in Cryo-electron Tomograms. Bioinformatics (2020). doi:10.1093/bioinformatics/btaa671 . arXiv:2007.15422
  12. Liu S, Ban X, Zeng X, Zhao F, Gao Y, Wu W, Zhang H, Chen F, Hall T, Gao X, Xu Min. A Unified Framework for Packing Deformable and Non-deformable Subcellular Structures in Crowded Cryo-electron Tomogram Simulation. BMC Bioinformatics (2020).
  13. Gubins I, et al. SHREC’20 Benchmark: Classification in cryo-electron tomograms. Computers & Graphics. 2020. doi:10.1016/j.cag.2020.07.010
  14. Chen F, Jiang Y, Zeng X, Zhang J, Gao X, Xu M. PUB-SalNet: A Pre-Trained Unsupervised Self-Aware Backpropagation Network for Biomedical Salient Segmentation. Algorithms. 2020. doi:10.3390/a13050126
  15. Gao S, Han R, Zeng X, Xu M, Zhang F. Dilated-denseNet for macromolecule classification in cryo-electron tomography. International Symposium on Bioinformatics Research and Applications (ISBRA 2020). doi:10.1007/978-3-030-57821-3_8
  16. Zeng X, Xu M. Gum-Net: Unsupervised geometric matching for fast and accurate 3D subtomogram image alignment and averaging. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR 2020). Paper
  17. Shi J, Zeng X, Jiang R, Jiang T, Xu M. A simulated annealing approach for resolution guided homogeneous cryo electron microscopy image selection. Quantitative Biology. doi:10.1007/s40484-019-0191-8. Paper.
  18. Zeng X, Xu M. AITom: Open-source AI platform for cryo-electron tomography data analysis. (2019) arXiv:1911.03044
  19. Lu Y, Zeng X, Tian X, Shi X, Wang H, Zheng X, Liu X, Zhao X, Gao X, Xu M. Spark-based parallel calculation of 3D Fourier shell correlation for macromolecule structure local resolution estimation. BMC Bioinformatics. doi:10.1186/s12859-020-03680-6
  20. Wu X, Zeng X, Zhu Z, Gao X, Xu M. (2019) Template-Based and Template-Free Approaches in Cellular Cryo-Electron Tomography Structural Pattern Mining. In: Computational Biology, (Husi H ed), Codon Publications, doi:10.15586/computationalbiology.2019.ch11
  21. Che C, Xian Z, Zeng X, Gao X, Xu M. Domain Randomization for Macromolecule Structure Classification and Segmentation in Electron Cyro-tomograms. IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2019)
  22. Wu X, Mao Y, Wang H, Zeng X, Gao X, Xing E, Xu M. Regularized Adversarial Training (RAT) for Robust Cellular Electron Cryo Tomograms Classification. IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2019)
  23. Du X, Zeng X, Zhou B, Singh A, Xu M. Open-set Recognition of Unseen Macromolecules in Cellular Electron Cryo-Tomograms by Soft Large Margin Centralized Cosine Loss. British Machine Vision Conference (BMVC 2019 spotlight with acceptance rate < 5%). pdf
  24. Liu S, Du X, Xi R, Xu F, Zeng X, Zhou B, Xu M. Semi-supervised Macromolecule Structural Classification in Cellular Electron Cryo-Tomograms using 3D Autoencoding Classifier. British Machine Vision Conference (BMVC 2019). pdf
  25. Lu Y, Zeng X, Zhao X, Li S, Li H, Gao X, Xu M. Fine-grained Alignment of Cryo-electron Subtomograms Based on MPI Parallel Optimization. BMC Bioinformatics (2019) 20:443. doi:10.1186/s12859-019-3003-2
  26. Lin R, Zeng X, Kitani K, Xu M. Adversarial domain adaptation for cross data source macromolecule in situ structural classification in cellular electron cryo-tomograms. ISMB 2019. Bioinformatics. 2019 Jul 5; 35(14); i260–i268. doi:10.1093/bioinformatics/btz364
  27. Han R, Bao Z, Zeng X, Niu T, Zhang F, Xu M, Gao X. A joint method for marker-free alignment of tilt series in electron tomography. ISMB 2019. Bioinformatics. 2019. doi:10.1093/bioinformatics/btz323
  28. Luo Z, Zeng X, Bao Z, Xu M. Deep Learning-Based Strategy For Macromolecules Classification with Imbalanced Data from Cellular Electron Cryotomography. International Joint Conference on Neural Networks (IJCNN 2019). arXiv:1908.09993
  29. Li R, Zeng X, Siegmund S, Lin R, Zhou B, Liu C, Wang K, Jiang R, Freyberg Z, Lv H, Xu M. Automatic Localization and Identification of Mitochondria in Cellular Electron Cryo-Tomography using Faster-RCNN. BMC Bioinformatics. 201920 (Suppl 3) :132 doi:10.1186/s12859-019-2650-7
  30. Gubins et al. Classification in Cryo-Electron Tomograms. Eurographics Workshop on 3D Object Retrieval. doi: 10.2312/3dor.20191061
  31. Zhao G, Zhou B, Wang K, Jiang R, Xu M. Respond-CAM: Analyzing Deep Models for 3D Imaging Data by Visualizations. Medical Image Computing & Computer Assisted Intervention (MICCAI) 2018. arXiv:1806.00102
  32. Liu C, Zeng X, Guo Q, Wang K, Xu M. Multi-task Learning for Macromolecule Classification, Segmentation and Coarse Structural Recovery in Cryo-Tomography. British Machine Vision Conference (BMVC) 2018. arXiv:1805.06332
  33. Wang K, Zeng X, Liang X, Huo Z, Xing E, Xu M. Image-derived generative modeling of pseudo-macromolecular structures - towards statistical assessment of electron cryotomography template matching. British Machine Vision Conference (BMVC) 2018. pdf . arXiv:1805.04634
  34. Liu C, Zeng X, Lin R, Liang X, Freyberg Z, Xing E, Xu M. Deep learning based supervised semantic segmentation of Electron Cryo-Subtomograms. IEEE International Conference on Image Processing (ICIP) 2018. arXiv:1802.04087
  35. Zhao Y, Zeng X, Guo Q, Xu M. An integration of fast alignment and maximum-likelihood methods for electron subtomogram averaging and classification. ISMB 2018. Bioinformatics. 2018 Jul 1; 34(13): i227–i236. doi:10.1093/bioinformatics/bty267. arXiv:1804.01203
  36. Guo J, Zhou B, Zeng X, Freyberg Z, Xu M. Model compression for faster structural separation of macromolecules captured by Cellular Electron Cryo-Tomography. arXiv:1801.10597. International Conference on Image Analysis and Recognition (ICIAR) 2018
  37. Zhou B, Guo Q, Zeng X, Gao X, Xu M. Feature Decomposition Based Saliency Detection in Electron Cryo-Tomograms. arXiv:1801.10562. IEEE International Conference on Bioinformatics & Biomedicine, Workshop on Machine Learning in High Resolution Microscopy (BIBM-MLHRM 2018)
  38. Che C, Lin R, Zeng X, Elmaaroufi K, Galeotti J, Xu M. Improved deep learning based macromolecules structure classification from electron cryo tomograms. Machine vision and applications 29.8 (2018): 1227-1236. doi:10.1007/s00138-018-0949-4. arXiv:1707.04885
  39. Zeng X, Leung M, Zeev-Ben-Mordehai T, Xu M. A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation . Journal of Structural Biology. 2018 May;202(2):150-160. doi:10.1016/j.jsb.2017.12.015 arXiv:1706.04970 [code]
  40. Xu M, Chai X, Muthakana H, Liang X, Yang G, Zeev-Ben-Mordehai T, Xing E. Deep learning based subdivision approach for large scale macromolecules structure recovery from electron cryo tomograms. 2017. arXiv:1701.08404. ISMB 2017 (acceptance rate 16%), Bioinformatics doi:10.1093/bioinformatics/btx230 [code]
  41. Xu M, Singla J, Tocheva E, Chang Y, Stevens R, Jensen G, Alber F. De novo structural pattern mining in cellular electron cryo-tomograms. Structure. 2019 Apr 2;27(4):679-691.e14. doi:10.1016/j.str.2019.01.005. (Appeared on Structure volume cover and highlighted in Nature Methods 16, page 285 (2019), doi:10.1038/s41592-019-0382-2)
  42. Frazier Z, Xu M, Alber F. TomoMiner and TomoMiner Cloud: A software platform for large-scale subtomogram structural analysis. Structure 2017. (doi: 10.1016/j.str.2017.04.016, co-corresponding author).
  43. Pei L, Xu M, Frazier Z, Alber F. Simulating Cryo-Electron Tomograms of Crowded Mixtures of Macromolecular Complexes and Assessment of Particle Picking. BMC Bioinformatics. 2016; 17: 405.
  44. Xu M, Alber F. Automated target segmentation and real space fast alignment methods for high-throughput classification and averaging of crowded cryo-electron subtomograms. ISMB/ECCB 2013, Bioinformatics. 2013 Jul 1;29(13):i274-82.
  45. Thalassinos K, Pandurangan AP, Xu M, Alber F, Topf M. Conformational States of macromolecular assemblies explored by integrative structure calculation. Structure. 2013 Sep 3;21(9):1500-8.
  46. Xu M, Beck M, Alber F. High-throughput subtomogram alignment and classification by Fourier space constrained fast volumetric matching. Journal of Structural Biology. 2012 May;178(2):152-64. Epub 2012 Mar 7.
  47. Xu M, Alber F. High precision alignment of cryo-electron subtomograms through gradient-based parallel optimization. BMC Systems Biology. 2012, 6(Suppl 1):S18
  48. Xu M, Beck M, Alber F. Template-free detection of macromolecular complexes in cryo-electron tomograms. Bioinformatics (ISMB 2011). 2011 Jul 1;27(13):i69-i76.
  49. Beck M, Topf M, Frazier Z, Tjong H, Xu M, Zhang S, Alber F. Exploring the Spatial and Temporal Organization of a Cell’s Proteome. Journal of Structural Biology. 2011 Mar; 173(3):483-496.
  50. Zhang S, Vasishtan D, Xu M, Topf M, Alber F. A fast mathematical programming procedure for simultaneous fitting of assembly components into cryo-EM density maps. Bioinformatics (ISMB 2010). 2010 Jun 15;26(12):i261-8.
  51. Xu M, Zhang S, Alber F. 3D rotation invariant features for characterization of molecular density map images. IEEE International Conference on Bioinformatics & Biomedicine (BIBM 2009)

Spatial transcriptomics

  1. Cang Z, Ning X, Nie A, Xu M, Zhang J. Scan-IT: Domain segmentation of spatial transcriptomics images by graph neural network. British Machine Vision Conference (BMVC) 2021

Computer vision & Machine learning

  1. Wang T, Li X, Yang P, Hu G, Zeng X, Huang S, Xu C, Xu M. Boosting Active Learning via Improving Test Performance. AAAI Conference on Artificial Intelligence. (AAAI 2022)
  2. Yang Y, Ma Y, Zhang J, Gao X, Xu M. AttPNet: Attention-Based Deep Neural Network for 3D Point Set Analysis. Sensors. doi:10.3390/s20195455
  3. Pang J, Yi K, Yin W, Xu M. Experimental Analysis of Legendre Decomposition in Machine Learning. arXiv:2008.05095

Biomedical image analysis

  1. Zhang B, Yang K, Xu M, Wu J, Cheng C. Deep learning predicts EBV status in gastric cancer based on spatial patterns of lymphocyte infiltration. Cancers. doi:10.3390/cancers13236002
  2. Dong N, Kampffmeyer M, Liang X, Xu M, Voiculescu I, Xing E. Towards robust partially supervised multi-structure medical image segmentation on small-scale data. Applied Soft Computing. doi:10.1016/j.asoc.2021.108074 arXiv:2011.14164
  3. Dong N, Xu M, Liang X, Jiang Y, Dai W, Xing E. Neural Architecture Search for Adversarial Medical Image Segmentation. Medical Image Computing & Computer Assisted Intervention (MICCAI 2019).
  4. Xiao Q, Zou J, Yang M, Gaudio A, Kitani K, Smailagic A, Costa P, Xu M. Improving Lesion Segmentation for Diabetic Retinopathy Using Adversarial Learning. International Conference on Image Analysis and Recognition (ICIAR 2019)
  5. Wang W, Taft D, Chen Y, Zhang J, Wallace C, Xu M, Watkins S, Xing J. Learn to segment single cells with deep distance estimator and deep cell detector. Computers in Biology and Medicine. doi:10.1016/j.compbiomed.2019.04.006
  6. Wang Z, Dong N, DRosario S, Xu M, Xie P, Xing E. Ellipse detection of optic disc-and-cup boundary in fundas image with unsupervised domain adaptation. IEEE International Symposium on Biomedical Imaging (ISBI 2019)


  1. Chen Z, Zhang J, Liu J, Zhang Z, Zhu J, Xu M, Gerstein M. SCAN-ATAC-Sim: a scalable and efficient method for simulating single-cell ATAC-seq data from bulk-tissue experiments. Bioinformatics.
  2. Zheng Y, Wang H, Zhang Y, Gao X, Xing E, Xu M. Poly(A)-DG: a deep-learning-based domain generalization method to identify cross-species Ploy(A) signal without prior knowledge from target species. PLOS Computational Biology. doi:10.1371/journal.pcbi.1008297
  3. Xu M, Li W, James GM, Mehan MR, Zhou XJ. Automated multidimensional phenotype profiling using large public microarray repositories. Proc Natl Acad Sci U S A. (PNAS). 2009; 106(30), 12323 - 12328. (Highlighted in Nature Methods 6, 632; Selected and re-published in 2010 International Medical Informatics Association Yearbook of Medical Informatics)
  4. Xu M, Kao MJ, Nunez-Iglesias J, Nevins JR, West M, Zhou XJ. An integrative approach to characterize disease-specific pathways and their coordination: a case study in cancer. BMC Genomics. 2008; 9 Suppl 1:S12.
  5. Xu M, Zhu M, Zhang L. A stable iterative method for refining discriminative gene clusters. BMC Genomics. 2008 Sep 16;9 Suppl 2:S18

Computational biology

  1. Wang H, Wei Y, Cao M, Xu M, Wu W, Xing E. Deep Inductive Matrix Completion for Biomedical Interaction Prediction. IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2019, acceptance rage 18%)