| Accounting for technical noise in single-cell RNA-seq experiments P Brennecke, S Anders, JK Kim, AA Kołodziejczyk, X Zhang, V Proserpio, ... Nature methods 10 (11), 1093-1095, 2013 | 1042 | 2013 |
| Single-cell RNA sequencing reveals T helper cells synthesizing steroids de novo to contribute to immune homeostasis B Mahata, X Zhang, AA Kolodziejczyk, V Proserpio, L Haim-Vilmovsky, ... Cell reports 7 (4), 1130-1142, 2014 | 222 | 2014 |
| Simulating multiple faceted variability in single cell RNA sequencing X Zhang, C Xu, N Yosef Nature communications 10 (1), 2611, 2019 | 123 | 2019 |
| Evolution of oligomeric state through allosteric pathways that mimic ligand binding T Perica, Y Kondo, SP Tiwari, SH McLaughlin, KR Kemplen, X Zhang, ... Science 346, 2014 | 76 | 2014 |
| Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation V Proserpio, A Piccolo, L Haim-Vilmovsky, G Kar, T Lönnberg, ... Genome Biology 17 (1), 103, 2016 | 68 | 2016 |
| CD4+ and CD8+ cytotoxic T lymphocytes may induce mesenchymal cell apoptosis in IgG4-related disease CA Perugino, N Kaneko, T Maehara, H Mattoo, J Kers, H Allard-Chamard, ... Journal of Allergy and Clinical Immunology 147 (1), 368-382, 2021 | 64 | 2021 |
| Single-cell RNA-sequencing resolves self-antigen expression during mTEC development RJ Miragaia, X Zhang, T Gomes, V Svensson, T Ilicic, J Henriksson, G Kar, ... Scientific Reports 8, 685, 2018 | 49 | 2018 |
| Evolution of protein structures and interactions from the perspective of residue contact networks X Zhang, T Perica, SA Teichmann Current opinion in structural biology 23 (6), 954-963, 2013 | 48 | 2013 |
| scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously Z Zhang, C Yang, X Zhang Genome biology 23 (1), 139, 2022 | 45* | 2022 |
| Inference of high-resolution trajectories in single-cell RNA-seq data by using RNA velocity Z Zhang, X Zhang Cell Reports Methods 1 (6), 2021 | 34* | 2021 |
| Refining transcriptional regulatory networks using network evolutionary models and gene histories X Zhang, BME Moret Algorithms for Molecular Biology 5 (1), 1, 2010 | 24 | 2010 |
| GRNUlar: a deep learning framework for recovering Single-Cell gene regulatory networks H Shrivastava, X Zhang, L Song, S Aluru Journal of Computational Biology 29 (1), 27-44, 2022 | 22 | 2022 |
| Boosting the performance of inference algorithms for transcriptional regulatory networks using a phylogenetic approach X Zhang, B Moret Algorithms in Bioinformatics, 245-258, 2008 | 15 | 2008 |
| VeloSim: Simulating single cell gene-expression and RNA velocity Z Zhang, X Zhang bioRxiv, 2021.01. 11.426277, 2021 | 14 | 2021 |
| Grnular: gene regulatory network reconstruction using unrolled algorithm from single cell rna-sequencing data H Shrivastava, X Zhang, S Aluru, L Song bioRxiv, 2020.04. 23.058149, 2020 | 13 | 2020 |
| scMoMaT jointly performs single cell mosaic integration and multi-modal bio-marker detection Z Zhang, H Sun, R Mariappan, X Chen, X Chen, MS Jain, M Efremova, ... Nature Communications 14 (1), 384, 2023 | 12 | 2023 |
| CLARIFY: cell–cell interaction and gene regulatory network refinement from spatially resolved transcriptomics M Bafna, H Li, X Zhang Bioinformatics 39 (Supplement_1), i484-i493, 2023 | 11 | 2023 |
| Refining regulatory networks through phylogenetic transfer of information X Zhang, BME Moret IEEE/ACM transactions on computational biology and bioinformatics 9 (4 …, 2012 | 11 | 2012 |
| scMultiSim: simulation of multi-modality single cell data guided by cell-cell interactions and gene regulatory networks H Li, Z Zhang, M Squires, X Chen, X Zhang Research Square, 2022 | 10 | 2022 |
| TedSim: temporal dynamics simulation of single-cell RNA sequencing data and cell division history X Pan, H Li, X Zhang Nucleic acids research 50 (8), 4272-4288, 2022 | 8 | 2022 |
Sarah A. TeichmannWellcome Sanger Institute & University of Cambridge在 cam.ac.uk 的电子邮件经过验证
