Wei Shao

发表

Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma

Zhi Han, Jie Zhang, Kun Huang, 2020, Nature Communications.

BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes

Travis S. Johnson, Jie Zhang, Kun Huang, 2019, Genome Biology.

Application of unsupervised deep learning algorithms for identification of specific clusters of chronic cough patients from EMR data

Zhi Han, Wei Shao, V. Turzhitsky, 2022, BMC Bioinformatics.

Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease

Travis S. Johnson, Christina Y. Yu, Jie Zhang, 2020, Genome Medicine.

Electrospun PVA/gelatin Based Nanofiber Membranes with Synergistic Antibacterial Performance

Wei Shao, Lei Jiang, Sirui He, 2021, Colloids and Surfaces A: Physicochemical and Engineering Aspects.

regSNPs-ASB: A Computational Framework for Identifying Allele-Specific Transcription Factor Binding From ATAC-seq Data

Christina Y. Yu, Weixing Feng, Yunlong Liu, 2020, Frontiers in Bioengineering and Biotechnology.

Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data

Zhi Han, Jie Zhang, Kun Huang, 2020, JCO clinical cancer informatics.

Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer

Christina Y. Yu, Weixing Feng, Yunlong Liu, 2020, BMC Medical Genomics.

A Deep Learning Approach for Tissue Spatial Quantification and Genomic Correlations of Histopathological Images

Zhi Han, Jie Zhang, Kun Huang, 2020, bioRxiv.

Preparation and characterization of self-healable and wearable hydrogels with ultrasensitive sensing performances

Wei Shao, Lei Jiang, Sirui He, 2022, Composites Part B: Engineering.

Preparation of ε-polylysine and hyaluronic acid self-assembled microspheres loaded bacterial cellulose aerogels with excellent antibacterial activity

Wei Shao, Jia Liu, Jie Zhang, 2022, Colloids and Surfaces A: Physicochemical and Engineering Aspects.

Low-Rank Reorganization via Proportional Hazards Non-negative Matrix Factorization Unveils Survival Associated Gene Clusters

Jie Zhang, Kun Huang, P. Salama, 2020, ArXiv.

Preparation and characterization of novel cellulose based adsorbent with ultra-high methylene blue adsorption performance

Wei Shao, Jia Liu, Jie Zhang, 2022, Materials Chemistry and Physics.

Bimetallic MOFs loaded cellulose as an environment friendly bioadsorbent for highly efficient tetracycline removal.

Wei Shao, Jia Liu, Jie Zhang, 2022, International journal of biological macromolecules.

BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes

Travis S. Johnson, Kun Huang, J. Zhang, 2019, Genome Biology.

Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease

Travis S. Johnson, Christina Y. Yu, Jie Zhang, 2022, Genome Medicine.

Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma

Zhi Han, Jie Zhang, Kun Huang, 2020, Nature Communications.

Multi-task multi-modal learning for joint diagnosis and prognosis of human cancers

Liang Sun, Zhi Huang, Kun Huang, 2020, Medical Image Anal..

TSUNAMI: Translational Bioinformatics Tool Suite for Network Analysis and Mining

Maher Rizkalla, Zhi Han, Kun Huang, 2019, bioRxiv.

MOGONET integrates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification

Kun Huang, Wei Shao, Jie Zhang, 2021, Nature Communications.

MORONET: Multi-omics Integration via Graph Convolutional Networks for Biomedical Data Classification

Zhi Huang, Kun Huang, Zhengming Ding, 2020, bioRxiv.

Recent Advances of Deep Learning for Computational Histopathology: Principles and Applications

Daoqiang Zhang, Kun Huang, J. Zhang, 2022, Cancers.

TPSC: a module detection method based on topology potential and spectral clustering in weighted networks and its application in gene co-expression module discovery

Kun Huang, Wei Shao, Christina Y. Yu, 2021, BMC Bioinformatics.

Towards Fair Cross-Domain Adaptation via Generative Learning

Kun Huang, Wei Shao, Tongxin Wang, 2020, 2021 IEEE Winter Conference on Applications of Computer Vision (WACV).

Hyper-graph based Sparse Canonical Correlation Analysis for the Diagnosis of Alzheimer's Disease from Multi-dimensional Genomic Data.

Kun Huang, Zuoyi Zhang, Jie Zhang, 2020, Methods.

BrcaSeg: A Deep Learning Approach for Tissue Quantification and Genomic Correlations of Histopathological Images

Zhi Han, Jie Zhang, Kun Huang, 2021, Genom. Proteom. Bioinform..

Transfer Learning via Optimal Transportation for Integrative Cancer Patient Stratification

Kun Huang, Wei Shao, Min Zhang, 2021, IJCAI.

Identify Consistent Imaging Genomic Biomarkers for Characterizing the Survival-Associated Interactions Between Tumor-Infiltrating Lymphocytes and Tumors

Daoqiang Zhang, Kun Huang, Yawen Wu, 2022, MICCAI.

Optimal Transport-Based Early Detection of Mild Cognitive Impairment Patients Based on Magnetic Resonance Images

Travis S. Johnson, Jie Zhang, Kun Huang, 2021 .

Artificial intelligence reveals features associated with breast cancer neoadjuvant chemotherapy responses from multi-stain histopathologic images

Zhi Han, Kun Huang, J. Zhang, 2023, npj Precision Oncology.

Integrative Analysis of Pathological Images and Multi-Dimensional Genomic Data for Early-Stage Cancer Prognosis

Jun Cheng, Kun Huang, Liang Sun, 2020, IEEE Transactions on Medical Imaging.

Optimal transport- and kernel-based early detection of mild cognitive impairment patients based on magnetic resonance and positron emission tomography images

Travis S. Johnson, Jie Zhang, Kun Huang, 2022, Alzheimer's research & therapy.

Diagnostic Evidence GAuge of Single cells (DEGAS): A flexible deep-transfer learning framework for prioritizing cells in relation to disease

Zhi Huang, Kun Huang, Yijie Wang, 2020, bioRxiv.

Weakly Supervised Deep Ordinal Cox Model for Survival Prediction From Whole-Slide Pathological Images

Kun Huang, Zhi Han, Wei Shao, 2021, IEEE Transactions on Medical Imaging.

Applying interpretable deep learning models to identify chronic cough patients using EHR data

Kun Huang, Paul R. Dexter, Vladimir Turzhitsky, 2021, Comput. Methods Programs Biomed..

A Deep Learning Approach for Tissue Spatial Quantification

Jie Zhang, Kun Huang, Qianjin Feng, 2020 .

Diagnostic Evidence GAuge of Single cells (DEGAS): A flexible deep-transfer learning 4 framework for prioritizing cells in relation to disease

Xiaoqing Huang, Siwen Xu, Wei Shao, 2021 .