| An accurate and robust imputation method scImpute for single-cell RNA-seq data WV Li, JJ Li Nature communications 9 (1), 997, 2018 | 664 | 2018 |
| Immune suppressive landscape in the human esophageal squamous cell carcinoma microenvironment Y Zheng, Z Chen, Y Han, L Han, X Zou, B Zhou, R Hu, J Hao, S Bai, ... Nature communications 11 (1), 6268, 2020 | 279 | 2020 |
| scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured T Sun, D Song, WV Li, JJ Li Genome biology 22 (1), 163, 2021 | 82 | 2021 |
| Modeling and analysis of RNA‐seq data: a review from a statistical perspective WV Li, JJ Li Quantitative Biology 6 (3), 195-209, 2018 | 72 | 2018 |
| A statistical simulator scDesign for rational scRNA-seq experimental design WV Li, JJ Li Bioinformatics 35 (14), i41–i50, 2019 | 63 | 2019 |
| mbImpute: an accurate and robust imputation method for microbiome data R Jiang, WV Li, JJ Li Genome biology 22 (1), 192, 2021 | 41 | 2021 |
| Maternal cecal microbiota transfer rescues early-life antibiotic-induced enhancement of type 1 diabetes in mice XS Zhang, YS Yin, J Wang, T Battaglia, K Krautkramer, WV Li, J Li, ... Cell host & microbe 29 (8), 1249-1265. e9, 2021 | 39 | 2021 |
| sclink: Inferring sparse gene co-expression networks from single-cell expression data WV Li, Y Li Genomics, Proteomics & Bioinformatics 19 (3), 475-492, 2021 | 38 | 2021 |
| scImpute: accurate and robust imputation for single cell RNA-seq data WV Li, JJ Li BioRxiv, 141598, 2017 | 30 | 2017 |
| Benchmarking cell-type clustering methods for spatially resolved transcriptomics data A Cheng, G Hu, WV Li Briefings in bioinformatics 24 (1), bbac475, 2023 | 29 | 2023 |
| Selecting gene features for unsupervised analysis of single-cell gene expression data J Sheng, WV Li Briefings in bioinformatics 22 (6), bbab295, 2021 | 26 | 2021 |
| TROM: A testing-based method for finding transcriptomic similarity of biological samples WV Li, Y Chen, JJ Li Statistics in biosciences 9, 105-136, 2017 | 24 | 2017 |
| Predicting long-term multicategory cause of death in patients with prostate cancer: random forest versus multinomial model J Wang, F Deng, F Zeng, AJ Shanahan, WV Li, L Zhang American journal of cancer research 10 (5), 1344, 2020 | 21 | 2020 |
| scINSIGHT for interpreting single-cell gene expression from biologically heterogeneous data K Qian, S Fu, H Li, WV Li Genome biology 23 (1), 82, 2022 | 19 | 2022 |
| Trends and prediction in daily incidence of novel coronavirus infection in China, Hubei Province and Wuhan City: an application of Farr’s law J Xu, Y Cheng, X Yuan, WV Li, L Zhang American journal of translational research 12 (4), 1355, 2020 | 18 | 2020 |
| MAAPER: model-based analysis of alternative polyadenylation using 3′ end-linked reads WV Li, D Zheng, R Wang, B Tian Genome Biology 22, 222, 2021 | 15 | 2021 |
| MSIQ: joint modeling of multiple RNA-seq samples for accurate isoform quantification WV Li, A Zhao, S Zhang, JJ Li The annals of applied statistics 12 (1), 510, 2018 | 10 | 2018 |
| AIDE: annotation-assisted isoform discovery with high precision WV Li, S Li, X Tong, L Deng, H Shi, JJ Li Genome research 29 (12), 2056-2072, 2019 | 9 | 2019 |
| scdesign2: an interpretable simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured T Sun, D Song, WV Li, JJ Li bioRxiv, 2020.11. 17.387795, 2020 | 8 | 2020 |
| Epigenome overlap measure (EPOM) for comparing tissue/cell types based on chromatin states WV Li, ZS Razaee, JJ Li BMC genomics 17, 109-125, 2016 | 8 | 2016 |
Jingyi Jessica LiProfessor, Department of Statistics, University of California at Los Angeles (UCLA)在 stat.ucla.edu 的电子邮件经过验证
