Reversed graph embedding resolves complex single-cell trajectories

Qiu, Xiaojie, Mao, Qi, Tang, Ying, Wang, Li, Chawla, Raghav, Pliner, Hannah A, Trapnell, Cole·2017·Nature Methods

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  7. SuperCT: a supervised-learning framework for enhanced characterization of single-cell transcriptomic profiles
    Xie, Peng, Gao, Mingxuan, Wang, Chunming, Zhang, Jianfei, Noel, Pawan, Yang, Chaoyong, Von Hoff, Daniel, Han, Haiyong, Zhang, Michael Q, Lin, Wei · 2019 · Nucleic Acids Research
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    Cates, Kitra, McCoy, Matthew J., Kwon, Ji-Sun, Liu, Yangjian, Abernathy, Daniel G., Zhang, Bo, Liu, Shaopeng, Gontarz, Paul, Kim, Woo Kyung, Chen, Shawei et al. · 2021 · Cell Stem Cell
  12. An interpretable deep-learning architecture of capsule networks for identifying cell-type gene expression programs from single-cell RNA-sequencing data
    Wang, Lifei, Nie, Rui, Yu, Zeyang, Xin, Ruyue, Zheng, Caihong, Zhang, Zhang, Zhang, Jiang, Cai, Jun · 2020 · Nature Machine Intelligence
  13. Uncovering axes of variation among single-cell cancer specimens
    Chen, William S., Zivanovic, Nevena, van Dijk, David, Wolf, Guy, Bodenmiller, Bernd, Krishnaswamy, Smita · 2020 · Nature Methods
  14. Dissecting key regulators of transcriptome kinetics through scalable single-cell RNA profiling of pooled CRISPR screens
    Xu, Zihan, Sziraki, Andras, Lee, Jasper, Zhou, Wei, Cao, Junyue · 2024 · Nature Biotechnology
  15. Generative modeling of single-cell gene expression for dose-dependent chemical perturbations
    Kana, Omar, Nault, Rance, Filipovic, David, Marri, Daniel, Zacharewski, Tim, Bhattacharya, Sudin · 2023 · Patterns
  16. Network control principles for identifying personalized driver genes in cancer
    Guo, Wei-Feng, Zhang, Shao-Wu, Zeng, Tao, Akutsu, Tatsuya, Chen, Luonan · 2020 · Briefings in Bioinformatics
  17. Differentiation reveals latent features of aging and an energy barrier in murine myogenesis
    Kimmel, Jacob C., Yi, Nelda, Roy, Margaret, Hendrickson, David G., Kelley, David R. · 2021 · Cell Reports
  18. Exercise modifies the transcriptional regulatory features of monocytes in Alzheimer’s patients: a multi-omics integration analysis based on single cell technology
    Chen, Yisheng, Sun, Yaying, Luo, Zhiwen, Chen, Xiangjun, Wang, Yi, Qi, Beijie, Lin, Jinrong, Lin, Wei-Wei, Sun, Chenyu, Zhou, Yifan et al. · 2022 · Frontiers in Aging Neuroscience
  19. Single-Cell Computational Strategies for Lineage Reconstruction in Tissue Systems
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  20. Region-specific cellular and molecular basis of liver regeneration after acute pericentral injury.
    Wang, Shuyong, Wang, Xuan, Shan, Yiran, Tan, Zuolong, Su, Yuxin, Cao, Yannan, Wang, Shuang, Dong, Jiahong, Gu, Jin, Wang, Yunfang · 2024 · Cell Stem Cell
  21. Spatiotemporal transcriptomics elucidates the pathogenesis of fulminant viral myocarditis
    Li, Huihui, Chen, Xueting, Wang, James Jiqi, Shen, Juan, Abuduwufuer, Kudusi, Zhang, Zhao, Dong, Zhensheng, Wen, Zheng, He, Jingwei, Chen, Silian et al. · 2025 · Signal Transduction and Targeted Therapy
  22. Multidirectional characterization of cellular composition and spatial architecture in human multiple primary lung cancers
    Wang, Yawei, Chen, Di, Liu, Yu, Shi, Daiwang, Duan, Chao, Li, Jinghan, Shi, Xiang, Zhang, Yong, Yu, Zhanwu, Sun, Nan et al. · 2023 · Cell Death & Disease
  23. Lung endothelium exploits susceptible tumor cell states to instruct metastatic latency
    Jakab, Moritz, Lee, Ki Hong, Uvarovskii, Alexey, Ovchinnikova, Svetlana, Kulkarni, Shubhada R., Jakab, Sevinç, Rostalski, Till, Spegg, Carleen, Anders, Simon, Augustin, Hellmut G. · 2024 · Nature Cancer
  24. Squidiff: predicting cellular development and responses to perturbations using a diffusion model
    He, Siyu, Zhu, Yuefei, Tavakol, Daniel Naveed, Ye, Haotian, Lao, Yeh-Hsing, Zhu, Zixian, Xu, Cong, Chauhan, Shradha, Garty, Guy, Tomer, Raju et al. · 2026 · Nature Methods
  25. A Comprehensive Survey of Statistical Approaches for Differential Expression Analysis in Single-Cell RNA Sequencing Studies
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  26. Occult polyclonality of preclinical pancreatic cancer models drives in vitro evolution
    Monberg, Maria E., Geiger, Heather, Lee, Jaewon J., Sharma, Roshan, Semaan, Alexander, Bernard, Vincent, Wong, Justin, Wang, Fang, Liang, Shaoheng, Swartzlander, Daniel B. et al. · 2022 · Nature Communications
  27. Cancer Cells Enter an Adaptive Persistence to Survive Radiotherapy and Repopulate Tumor
    Zhao, Yucui, Lu, Tingting, Song, Yanwei, Wen, Yanqin, Deng, Zheng, Fan, Jiahui, Zhao, Minghui, Zhao, Ruyi, Luo, Yuntao, xie, Jianzhu et al. · 2023 · Advanced Science
  28. APOE3 Christchurch modulates β-catenin/Wnt signaling in iPS cell-derived cerebral organoids from Alzheimer’s cases
    Perez-Corredor, Paula, Vanderleest, Timothy E., Vacano, Guido N., Sanchez, Justin S., Villalba-Moreno, Nelson D., Marino, Claudia, Krasemann, Susanne, Mendivil-Perez, Miguel A., Aguillón, David, Jiménez-Del-Río, Marlene et al. · 2024 · Frontiers in Molecular Neuroscience
  29. Differential gene expression analysis for multi-subject single-cell RNA-sequencing studies with<i>aggregateBioVar</i>
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  30. Targeting tumor–stromal interactions in triple-negative breast cancer using a human vascularized micro-tumor model
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  31. Chromatin accessibility dynamics of myogenesis at single cell resolution
    Pliner, Hannah A., Packer, Jonathan, McFaline-Figueroa, José L., Cusanovich, Darren A., Daza, Riza, Srivatsan, Sanjay, Qiu, Xiaojie, Jackson, Dana, Minkina, Anna, Adey, Andrew et al. · 2017
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  33. Agouti and BMP signaling drive a naturally occurring fate conversion of melanophores to leucophores in zebrafish
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  34. SenPred: a single-cell RNA sequencing-based machine learning pipeline to classify deeply senescent dermal fibroblast cells for the detection of an in vivo senescent cell burden
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  36. Cellular senescence in human liver under normal aging and cancer
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  41. Type 1 interferon perturbates clonal competition by reshaping human blood development
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