activity
20172021
most citedA convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation

53 citations · 172 across the 13 of their papers we have counts for

collaborators

13 papers

q-bio.QM2021★ 14 cited

Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography

Xuefeng Du, Haohan Wang, Zhenxi Zhu +4

Motivation: Cryo-Electron Tomography (cryo-ET) is a 3D bioimaging tool that visualizes the structural and spatial organization of macromolecules at a near-native state in single ce…

q-bio.QM2020★ 11 cited

Few shot domain adaptation for in situ macromolecule structural classification in cryo-electron tomograms

Liangyong Yu, Ran Li, Xiangrui Zeng +5

Motivation: Cryo-Electron Tomography (cryo-ET) visualizes structure and spatial organization of macromolecules and their interactions with other subcellular components inside singl…

q-bio.QM2019★ 9 cited

AITom: Open-source AI platform for cryo-electron tomography data analysis

Xiangrui Zeng, Min Xu

Cryo-electron tomography (cryo-ET) is an emerging technology for the 3D visualization of structural organizations and interactions of subcellular components at near-native state an…

stat.ME2019★ 1 cited

CS Sparse K-means: An Algorithm for Cluster-Specific Feature Selection in High-Dimensional Clustering

Xiangrui Zeng, Hongyu Zheng

Feature selection is an important and challenging task in high dimensional clustering. For example, in genomics, there may only be a small number of genes that are differentially e…

stat.ME2019★ 1 cited

Simultaneous Estimation of Number of Clusters and Feature Sparsity in Clustering High-Dimensional Data

Yujia Li, Xiangrui Zeng, Chien-Wei Lin +1

Estimating the number of clusters (K) is a critical and often difficult task in cluster analysis. Many methods have been proposed to estimate K, including some top performers using…

eess.IV2019★ 4 cited

Deep Learning-Based Strategy for Macromolecules Classification with Imbalanced Data from Cellular Electron Cryotomography

Ziqian Luo, Xiangrui Zeng, Zhipeng Bao +1

Deep learning model trained by imbalanced data may not work satisfactorily since it could be determined by major classes and thus may ignore the classes with small amount of data.…

cs.CV2018★ 10 cited

Multi-task Learning for Macromolecule Classification, Segmentation and Coarse Structural Recovery in Cryo-Tomography

Chang Liu, Xiangrui Zeng, Kaiwen Wang +2

Cellular Electron Cryo-Tomography (CECT) is a powerful 3D imaging tool for studying the native structure and organization of macromolecules inside single cells. For systematic reco…

q-bio.QM2018★ 13 cited

An integration of fast alignment and maximum-likelihood methods for electron subtomogram averaging and classification

Yixiu Zhao, Xiangrui Zeng, Qiang Guo +1

Motivation: Cellular Electron CryoTomography (CECT) is an emerging 3D imaging technique that visualizes subcellular organization of single cells at submolecular resolution and in n…

q-bio.QM2018★ 1 cited

Deep learning based supervised semantic segmentation of Electron Cryo-Subtomograms

Chang Liu, Xiangrui Zeng, Ruogu Lin +4

Cellular Electron Cryo-Tomography (CECT) is a powerful imaging technique for the 3D visualization of cellular structure and organization at submolecular resolution. It enables anal…

q-bio.QM2018★ 3 cited

Model compression for faster structural separation of macromolecules captured by Cellular Electron Cryo-Tomography

Jialiang Guo, Bo Zhou, Xiangrui Zeng +2

Electron Cryo-Tomography (ECT) enables 3D visualization of macromolecule structure inside single cells. Macromolecule classification approaches based on convolutional neural networ…

q-bio.QM2018★ 1 cited

Feature Decomposition Based Saliency Detection in Electron Cryo-Tomograms

Bo Zhou, Qiang Guo, Xiangrui Zeng +1

Electron Cryo-Tomography (ECT) allows 3D visualization of subcellular structures at the submolecular resolution in close to the native state. However, due to the high degree of str…

q-bio.QM2017★ 51 cited

Improved deep learning based macromolecules structure classification from electron cryo tomograms

Chengqian Che, Ruogu Lin, Xiangrui Zeng +3

Cellular processes are governed by macromolecular complexes inside the cell. Study of the native structures of macromolecular complexes has been extremely difficult due to lack of…

q-bio.QM2017★ 53 cited

A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation

Xiangrui Zeng, Miguel Ricardo Leung, Tzviya Zeev-Ben-Mordehai +1

Cellular electron cryo-tomography enables the 3D visualization of cellular organization in the near-native state and at submolecular resolution. However, the contents of cellular t…