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

53 citations · 65 across the 3 of their papers we have counts for

collaborators

10 papers

q-bio.QM2021

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.QM202011 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

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.ME20191 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

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

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.…