BASiCS: Bayesian Analysis of Single-Cell Sequencing Data

Cited by (304)

Items 101–200 of 304

1. RESCUE: imputing dropout events in single-cell RNA-sequencing data
   Samuel Tracy, Guo‐Cheng Yuan, Ruben Dries · 2019 · BMC Bioinformatics
2. Comprehensive evaluation of noise reduction methods for single-cell RNA sequencing data
   Shih‐Kai Chu, Shilin Zhao, Yu Shyr, Qi Liu · 2021 · Briefings in Bioinformatics
3. Controlling for Confounding Effects in Single Cell RNA Sequencing Studies Using both Control and Target Genes
   Mengjie Chen, Xiang Zhou · 2017 · Scientific Reports
4. A new lymphoid-primed progenitor marked by Dach1 downregulation identified with single cell multi-omics
   Daniela Amann‐Zalcenstein, Luyi Tian, Jaring Schreuder, Sara Tomei, Dawn S. Y. Lin, Kirsten A. Fairfax, Jessica E. Bolden, Mark D. McKenzie, Andrew Jarratt, Adrienne A. Hilton et al. · 2020 · Nature Immunology
5. Adaptation to ex vivo culture reduces human hematopoietic stem cell activity independently of the cell cycle
   Carys Johnson, Matthew Williams, Kendig Sham, Serena Belluschi, Wenjuan Ma, Xiaonan Wang, Winnie W. Y. Lau, Kerstin B. Kaufmann, Gabriela Krivdova, Emily F. Calderbank et al. · 2024 · Blood
6. SAVER: Gene expression recovery for UMI-based single cell RNA sequencing
   Mo Chao Huang, Jingshu Wang, Eduardo A. Torre, Hannah Dueck, Sydney Shaffer, Roberto Bonasio, John I. Murray, Arjun Raj, Mingyao Li, Nancy Ruonan Zhang · 2017 · bioRxiv (Cold Spring Harbor Laboratory)
7. A Comprehensive Survey of Statistical Approaches for Differential Expression Analysis in Single-Cell RNA Sequencing Studies
   Das, Samarendra, Rai, Anil, Merchant, Michael L., Cave, Matthew C., Rai, Shesh N. · 2021 · Genes
8. Quantifying and correcting bias in transcriptional parameter inference from single-cell data
   Ramon Grima, Pierre-Marie Esmenjaud · 2023 · Biophysical Journal
9. Computational approaches for high‐throughput single‐cell data analysis
   Helena Todorov, Yvan Saeys · 2018 · FEBS Journal
10. Understanding the complexity of retina and pluripotent stem cell derived retinal organoids with single cell RNA sequencing: current progress, remaining challenges and future prospective
    Darin Zerti, Joseph Collin, Rachel A. Queen, Simon Cockell, Majlinda Lako · 2019 · Current Eye Research
11. Selecting gene features for unsupervised analysis of single-cell gene expression data
    Jie Sheng, Wei Vivian Li · 2021 · Briefings in Bioinformatics
12. Transplanting rejuvenated blood stem cells extends lifespan of aged immunocompromised mice
    Sara Montserrat‐Vazquez, Noelle Ali, Francesca Matteini, Javier Lozano-Bartolomé, Zhaowei Tu, Eva Mejía-Ramírez, Gina Marka, Angelika Vollmer, Karin Soller, Mehmet Saçma et al. · 2022 · npj Regenerative Medicine
13. Heterogeneity of repolarization and cell-cell variability of cardiomyocyte Remodeling within the myocardial infarction border zone contribute to arrhythmia susceptibility
    Amoni, Matthew, Vermoortele, Dylan, Ekhteraei-Tousi, Samaneh, Doñate Puertas, Rosa, Gilbert, Guillaume, Youness, Mohamad, Thienpont, Bernard, Willems, Rik, Roderick, H. Llewelyn, Claus, Piet et al. · 2023 · Circulation: Arrhythmia and Electrophysiology
14. Data normalization for addressing the challenges in the analysis of single-cell transcriptomic datasets
    Raquel Cuevas‐Díaz Durán, Haichao Wei, Jiaqian Wu · 2024 · BMC Genomics
15. Flexible experimental designs for valid single-cell RNA-sequencing experiments allowing batch effects correction
    Fangda Song, Ga Ming Angus Chan, Yingying Wei · 2020 · Nature Communications
16. A mechanistic model for the negative binomial distribution of single-cell mRNA counts
    Lisa Amrhein, Kumar Harsha, Christiane Fuchs · 2019 · bioRxiv (Cold Spring Harbor Laboratory)
17. Modular bioinformatics analysis demonstrates that a Toll‑like receptor signaling pathway is involved in the regulation of macrophage polarization
    Biao Ma, Yang Yang, Zhituo Li, Dali Zhao, Weihui Zhang, Yanfeng Jiang, Dongbo Xue · 2018 · Molecular Medicine Reports
18. Dr.seq2: A quality control and analysis pipeline for parallel single cell transcriptome and epigenome data
    Chengchen Zhao, Shengen Shawn Hu, Xiao Huo, Yong Zhang · 2017 · PLoS ONE
19. Methods and challenges in the analysis of single-cell RNA-sequencing data
    Pablo G. Cámara · 2017 · Current Opinion in Systems Biology
20. Progress in Discovering Transcriptional Noise in Aging
    Josh Bartz, Hannim Jung, Karen R. Wasiluk, Lei Justan Zhang, Xiao Dong · 2023 · International Journal of Molecular Sciences
21. Exploring viral infection using single-cell sequencing
    Sylvie Rato, Monica Golumbeanu, Amalio Telenti, Angela Ciuffi · 2016 · Virus Research
22. Quantification of Inter-Sample Differences in T-Cell Receptor Repertoires Using Sequence-Based Information
    Ryo Yokota, Yuki Kaminaga, Tetsuya Kobayashi · 2017 · Frontiers in Immunology
23. Single-cell RNA-seq data clustering: A survey with performance comparison study
    Ruiyi Li, Jihong Guan, Shuigeng Zhou · 2020 · Journal of Bioinformatics and Computational Biology
24. distinct: A novel approach to differential distribution analyses
    Simone Tiberi, Helena Lucia Crowell, Pantelis Samartsidis, Lukas M. Weber, Mark D. Robinson · 2023 · The Annals of Applied Statistics
25. VarID2 quantifies gene expression noise dynamics and unveils functional heterogeneity of ageing hematopoietic stem cells
    Reyna Edith Rosales-Alvarez, Jasmin Rettkowski, Josip S. Herman, Gabrijela Dumbović, Nina Cabezas‐Wallscheid, Dominic Grün · 2023 · Genome biology
26. Bayesian statistical learning for big data biology
    Christopher Yau, Kieran R. Campbell · 2019 · Biophysical Reviews
27. COTAN: scRNA-seq data analysis based on gene co-expression
    Silvia Giulia Galfrè, Francesco Morandin, Marco Pietrosanto, Federico Cremisi, Manuela Helmer‐Citterich · 2021 · NAR Genomics and Bioinformatics
28. NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis
    Ankit Agrawal, Stefan Thomann, Sukanya Basu, Dominic Grün · 2024 · Nature Communications
29. Single-Cell RNA Sequencing of Human T Cells
    Alexandra–Chloé Villani, Karthik Shekhar · 2016 · Methods in molecular biology
30. Systematic mapping of organism-scale gene-regulatory networks in aging using population asynchrony
    Matthias Eder, Olivier M. F. Martin, Natasha Oswal, Lucia Sedlackova, Cátia Moutinho, Andrea Del Carmen-Fabregat, Simon Menendez Bravo, Arnau Sebé-Pedrós, Holger Heyn, Nicholas Stroustrup · 2024 · Cell
31. Insights from the Applications of Single-Cell Transcriptomic Analysis in Germ Cell Development and Reproductive Medicine
    Hyeonwoo La, Hyunjin Yoo, Eun Joo Lee, Nguyen Xuan Thang, Hee Jin Choi, Jeongheon Oh, Ji Hyun Park, Kwonho Hong · 2021 · International Journal of Molecular Sciences
32. sc-REnF: An entropy guided robust feature selection for single-cell RNA-seq data
    Snehalika Lall, Abhik Ghosh, Sumanta Ray, Sanghamitra Bandyopadhyay · 2021 · Briefings in Bioinformatics
33. Applications of Single-Cell Sequencing for Multiomics
    Yungang Xu, Xiaobo Zhou · 2018 · Methods in molecular biology
34. Generative modeling and latent space arithmetics predict single-cell perturbation response across cell types, studies and species
    Lotfollahi, M., Wolf, F. Alexander, Theis, Fabian J. · 2018
35. Integration tools for scRNA-seq data and spatial transcriptomics sequencing data
    Chaorui Yan, Yanxu Zhu, Miao Chen, Kainan Yang, Feifei Cui, Quan Zou, Zilong Zhang · 2024 · Briefings in Functional Genomics
36. CLEAR: coverage-based limiting-cell experiment analysis for RNA-seq
    Logan A. Walker, Michael G. Sovic, Chi‐Ling Chiang, Eileen Y. Hu, Jiyeon K. Denninger, Xi Chen, Elizabeth D. Kirby, John C. Byrd, Natarajan Muthusamy, Ralf A. Bundschuh et al. · 2020 · Journal of Translational Medicine
37. Solving stochastic gene-expression models using queueing theory: A tutorial review
    J. Szavits-Nossan, R. Grima · 2023 · Biophysical Journal
38. cgCorrect: a method to correct for confounding cell–cell variation due to cell growth in single-cell transcriptomics
    Blasi, Thomas, Buettner, Florian, Strasser, Michael K, Marr, Carsten, Theis, Fabian J · 2017 · Physical Biology
39. Single cell versus large population analysis: cell variability in elemental intracellular concentration and distribution
    Emil Malucelli, Alessandra Procopio, Michela Fratini, Alessandra Gianoncelli, A. Notargiacomo, Lucia Merolle, Azzurra Sargenti, Sara Castiglioni, Concettina Cappadone, Giovanna Farruggia et al. · 2017 · Analytical and Bioanalytical Chemistry
40. Dissecting the human immune system with single cell RNA sequencing technology
    Gang Xu, Yang Liu, Hanjie Li, Lei Liu, Shuye Zhang, Zheng Zhang · 2019 · Journal of Leukocyte Biology
41. Scedar: A scalable Python package for single-cell RNA-seq exploratory data analysis
    Yuanchao Zhang, Man Soo Kim, Erin Renée Reichenberger, Benjamin J. Stear, Deanne M. Taylor · 2020 · PLoS Computational Biology
42. The NSL complex-mediated nucleosome landscape is required to maintain transcription fidelity and suppression of transcription noise
    Kin Chung Lam, Ho‐Ryun Chung, Giuseppe Semplicio, Shantanu S. Iyer, Aline Gaub, Vivek Bhardwaj, Herbert Holz, Plamen Georgiev, Asifa Akhtar · 2019 · Genes & Development
43. Deep Learning Applications in Single-Cell Omics Data Analysis
    Nafiseh Erfanian, A. Ali Heydari, Pablo Iáñez Picazo, Afshin Derakhshani, Mohammad GhasemiGol, Mohsen Farahpour, Saeed Nasseri, Hossein Safarpour, Amirhossein Sahebkar · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
44. BEARscc determines robustness of single-cell clusters using simulated technical replicates
    David Tyler Severson, Richard Peter Owen, Michael Joseph White, Xin Lü, Benjamin Schuster‐Böckler · 2018 · Nature Communications
45. The progressive application of single-cell RNA sequencing technology in cardiovascular diseases
    Ke Yang, Jian-Yuan Huang, Ping Zhou, Yue Wang, Na Xing, Jian Yang, Kai-xuan Lin, Sun Yi-fan, Han-bin Lin, Rong Li · 2022 · Biomedicine & Pharmacotherapy
46. Built on sand: the shaky foundations of simulating single-cell RNA sequencing data
    Helena Lucia Crowell, Sarah X. Morillo Leonardo, Charlotte Soneson, Mark D. Robinson · 2021 · bioRxiv (Cold Spring Harbor Laboratory)
47. Toward uncharted territory of cellular heterogeneity: advances and applications of single-cell RNA-seq
    Brandon Lieberman, Meena Kusi, Chia‐Nung Hung, Chih‐Wei Chou, He Ning, Yen‐Yi Ho, Josephine Amalia Taverna, Tim H.‐M. Huang, Chun‐Liang Chen · 2020 · Journal of Translational Genetics and Genomics
48. scTIM: seeking cell-type-indicative marker from single cell RNA-seq data by consensus optimization
    Zhanying Feng, Xianwen Ren, Yuan Fang, Yining Yin, Chutian Huang, Zhao Yimin, Yong Wang · 2019 · Bioinformatics
49. Dimensionality reduction for single cell RNA sequencing data using constrained robust non-negative matrix factorization
    Shuqin Zhang, Yang Liu, Jinwen Yang, Zhixiang Lin, Michael K. Ng · 2020 · NAR Genomics and Bioinformatics
50. SwarnSeq: An improved statistical approach for differential expression analysis of single-cell RNA-seq data
    Samarendra Das, Shesh Nath Rai · 2021 · Genomics
51. Single-cell technologies and analyses in hematopoiesis and hematological malignancies
    Ignacio Campillo‐Marcos, Damiana Álvarez‐Errico, Regina Antoni Alandes, Elisabetta Mereu, Manel Esteller · 2021 · Experimental Hematology
52. Single‐cell technologies in reproductive immunology
    Jessica Vázquez, Irene M. Ong, Aleksandar K. Stanic · 2019 · American Journal of Reproductive Immunology
53. GPseudoRank: a permutation sampler for single cell orderings
    Magdalena E Strauß, John E. Reid, Lorenz Wernisch · 2018 · Bioinformatics
54. SDImpute: A statistical block imputation method based on cell-level and gene-level information for dropouts in single-cell RNA-seq data
    Jing Qi, Yang Zhou, Zicen Zhao, Shuilin Jin · 2021 · PLoS Computational Biology
55. Imputation Methods for scRNA Sequencing Data
    Mengyuan Wang, Jiatao Gan, Changfeng Han, Yanbing Guo, Kaihao Chen, Ya-zhou Shi, Bengong Zhang · 2022 · Applied Sciences
56. AdImpute: An Imputation Method for Single-Cell RNA-Seq Data Based on Semi-Supervised Autoencoders
    Xu Li, Yin Xu, Tong Xue, Xinyu Zhang, Jin Li · 2021 · Frontiers in Genetics
57. scPipe: a flexible R/Bioconductor preprocessing pipeline for single-cell RNA-sequencing data
    Luyi Tian, Shian Su, Xueyi Dong, Daniela Amann-Zalcenstein, Christine Biben, Azadeh Seidi, Douglas J. Hilton, Shalin H. Naik, Matthew E. Ritchie · 2017 · bioRxiv (Cold Spring Harbor Laboratory)
58. Single-cell RNA sequencing algorithms underestimate changes in transcriptional noise compared to single-molecule RNA imaging
    Neha Khetan, B. M. Zuckerman, Giuliana Calia, Xinyue Chen, Ximena Garcia Arceo, Leor S. Weinberger · 2024 · Cell Reports Methods
59. Multilevel Linear Models, Gibbs Samplers and Multigrid Decompositions (with Discussion)
    Giacomo Zanella, Gareth O. Roberts · 2020 · Bayesian Analysis
60. SCRaPL: A Bayesian hierarchical framework for detecting technical associates in single cell multiomics data
    Christos Maniatis, Catalina A. Vallejos, Guido Sanguinetti · 2022 · PLoS Computational Biology
61. scMMT: a multi-use deep learning approach for cell annotation, protein prediction and embedding in single-cell RNA-seq data
    Songqi Zhou, Yang Li, Wenyuan Wu, Li Li · 2024 · Briefings in Bioinformatics
62. Accurate Inference of Tumor Purity and Absolute Copy Numbers From High-Throughput Sequencing Data
    Xiguo Yuan, Zhe Li, Haiyong Zhao, Jun Bai, Junying Zhang · 2020 · Frontiers in Genetics
63. LAST-seq: single-cell RNA sequencing by direct amplification of single-stranded RNA without prior reverse transcription and second-strand synthesis
    Jun Lyu, Chongyi Chen · 2023 · Genome biology
64. Bivalent genes that undergo transcriptional switching identify networks of key regulators of embryonic stem cell differentiation
    Ah‐Jung Jeon, Greg Tucker‐Kellogg · 2020 · BMC Genomics
65. iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects
    Yunqing Liu, Jiayi Zhao, Taylor Sterling Adams, Ningya Wang, Jonas C. Schupp, Weimiao Wu, John E. McDonough, Geoffrey Lowell Chupp, Naftali Kaminski, Zuoheng Wang et al. · 2023 · BMC Bioinformatics
66. I-Impute: a self-consistent method to impute single cell RNA sequencing data
    Xikang Feng, Lingxi Chen, Zishuai Wang, Shuai Cheng Li · 2020 · BMC Genomics
67. scRNA-seq mixology: towards better benchmarking of single cell RNA-seq analysis methods
    Luyi Tian, Xueyi Dong, Saskia Freytag, Kim‐Anh Lê Cao, Shian Su, Abolfazl JalalAbadi, Daniela Amann‐Zalcenstein, Tom S. Weber, Azadeh Seidi, Jafar S. Jabbari et al. · 2018 · bioRxiv (Cold Spring Harbor Laboratory)
68. Single-Cell Informatics for Tumor Microenvironment and Immunotherapy
    Jiabao Tian, Xinyu Bai, Camelia Y. J. Quek · 2024 · International Journal of Molecular Sciences
69. Epigenetic drift score captures directional methylation variability and links aging to transcriptional, metabolic, and genetic alterations
    Xiu Fan, Qili Qian, Wenran Li, Tianzi Liu, Changqing Zeng, Peilin Jia, Huandong Lin, Xin Gao, Jin Li, Mingfeng Xia et al. · 2025 · Genome Research
70. Multimodal screen identifies noise-regulatory proteins
    Óscar García‐Blay, Xinyu Hu, Christin L. Wassermann, Tom van Bokhoven, Fréderique Struijs, Maike M. K. Hansen · 2024 · Developmental Cell
71. Big data analytics in single‐cell transcriptomics: Five grand opportunities
    N Bhattacharya, Colleen C. Nelson, Gaurav Ahuja, Debarka Sengupta · 2021 · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
72. Lessons from single-cell transcriptome analysis of oxygen-sensing cells
    Ting Zhou, Hiroaki Matsunami · 2017 · Cell and Tissue Research
73. Single-Cell Multi-Omics in Type 2 Diabetes Mellitus: Revealing Cellular Heterogeneity and Mechanistic Insights
    Yijie Wei, Feitong Hong, Sijia Xie, Xinwei Luo, Xiaolong Li, Fuying Dao, Kejun Deng, Hao Lin, Hao Lv · 2025 · International Journal of Molecular Sciences
74. The mechanisms shaping the single-cell transcriptional landscape
    Celia Pilar Martinez‐Jimenez, Duncan T. Odom · 2016 · Current Opinion in Genetics & Development
75. Analysis of microRNA Regulation in Single Cells
    Wendao Liu, Noam Shomron · 2021 · Methods in molecular biology
76. SMIXnorm: Fast and Accurate RNA-Seq Data Normalization for Formalin-Fixed Paraffin-Embedded Samples
    Shen Yin, Xiaowei Zhan, Bo Yao, Guanghua Xiao, Xinlei Wang, Yang Xie · 2021 · Frontiers in Genetics
77. Defining cell identity beyond the premise of differential gene expression
    Hani Jieun Kim, Patrick Tam, Pengyi Yang · 2021 · Cell Regeneration
78. GPseudoClust: deconvolution of shared pseudo-profiles at single-cell resolution
    Magdalena E Strauß, Paul Kirk, John E. Reid, Lorenz Wernisch · 2019 · Bioinformatics
79. SCHiRM: Single Cell Hierarchical Regression Model to detect dependencies in read count data
    Jukka Intosalmi, Henrik Mannerström, Saara Hiltunen, Harri J Lähdesmäki · 2018 · bioRxiv (Cold Spring Harbor Laboratory)
80. Single cell characterization of B-lymphoid differentiation and leukemic cell states during chemotherapy in ETV6-RUNX1 positive pediatric leukemia identifies drug-targetable transcription factor activities
    Juha Mehtonen, Susanna Teppo, Mari Lahnalampi, Aleksi Kokko, Riina Kaukonen, Laura Oksa, Maria Bouvy‐Liivrand, Alena Malyukova, Saara Laukkanen, Petri I. Mäkinen et al. · 2020 · bioRxiv (Cold Spring Harbor Laboratory)
81. Comparative analysis between RNA-seq and single-molecule RNA FISH indicates that the pyrimidine nucleobase idoxuridine (IdU) globally amplifies transcriptional noise
    Giuliana Calia, Xinyue Chen, Binyamin Zuckerman, Leor S. Weinberger · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
82. Income, education, and other poverty-related variables: A journey through Bayesian hierarchical models
    Irving G'omez-M'endez, Chainarong Amornbunchornvej · 2023 · Heliyon
83. A flexible network-based imputing-and-fusing approach towards the identification of cell types from single-cell RNA-seq data
    Qi Yang, Yang Guo, Huixin Jiao, Xuequn Shang · 2020 · BMC Bioinformatics
84. PseudoGA: cell pseudotime reconstruction based on genetic algorithm
    Pronoy Kanti Mondal, Udit Surya Saha, Indranil Mukhopadhyay · 2021 · Nucleic Acids Research
85. Uncertainty versus variability: Bayesian methods for analysis of scRNA-seq data
    Yuanhua Huang, Guido Sanguinetti · 2021 · Current Opinion in Systems Biology
86. Using Single Nucleotide Variations in Single-Cell RNA-Seq to Identify Subpopulations and Genotype-phenotype Linkage
    Olivier Poirion, Xun Zhu, Travers H. Ching, Lana X. Garmire · 2016 · bioRxiv (Cold Spring Harbor Laboratory)
87. Gene expression noise dynamics unveil functional heterogeneity of ageing hematopoietic stem cells
    Reyna Edith Rosales-Alvarez, Jasmin Rettkowski, Josip S. Herman, Gabrijela Dumbović, Nina Cabezas‐Wallscheid, Dominic Grün · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
88. Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling
    Manikandan Narayanan, Andrew J. Martins, John S. Tsang · 2016 · PLoS Computational Biology
89. Single-Cell Allele-Specific Gene Expression Analysis
    Meichen Dong, Yuchao Jiang · 2019 · Methods in molecular biology
90. A kernel non-negative matrix factorization framework for single cell clustering
    Hao Jiang, Ming Yi, Shihua Zhang · 2020 · Applied Mathematical Modelling
91. HyperChIP: identification of hypervariable signals across ChIP-seq or ATAC-seq samples
    Haojie Chen, Shiqi Tu, Chongze Yuan, Feng Tian, Yijing Zhang, Yihua Sun, Zhen Shao · 2022 · Genome biology
92. Shared Differential Clustering across Single-cell RNA Sequencing Datasets with the Hierarchical Dirichlet Process
    Jinlu Liu, Sara Wade, Natalia Bochkina · 2024 · Econometrics and Statistics
93. Cytomulate: accurate and efficient simulation of CyTOF data
    Yuqiu Yang, Kaiwen Wang, Zeyu Lu, Tao Wang, Xinlei Wang · 2023 · Genome biology
94. Comprehensive Analysis of RNA Expression Correlations between Biofluids and Human Tissues
    Ruya Sun, Chunmei Cui, Yuan Zhou, Qinghua Cui · 2021 · Genes
95. Gene expression noise in development: genome-wide dynamics
    Danique J. C. Bax, Jeske Strik, Lynn A.P. Schepens, Tineke Laura Lenstra, Maike M. K. Hansen, Hendrik Marks · 2026 · Trends in Genetics
96. From noise to models to numbers: Evaluating negative binomial models and parameter estimations in single-cell RNA-seq
    Yiling Wang, Zhanpeng Shu, Zhixing Cao, Ramon Grima · 2026 · PLoS Computational Biology
97. COMSE: analysis of single-cell RNA-seq data using community detection-based feature selection
    Qinhuan Luo, Yaozhu Chen, Xun Lan · 2024 · BMC Biology
98. scMTD: a statistical multidimensional imputation method for single-cell RNA-seq data leveraging transcriptome dynamic information
    Jing Qi, Qiongyu Sheng, Yang Zhou, Jiao Hua, Shutong Xiao, Shuilin Jin · 2022 · Cell & Bioscience
99. Imputation of Human Primary Osteoblast Single Cell RNA-Seq Data Identified Three Novel Osteoblastic Subtypes
    Hui-Xi Zhang, Chong Cao, Xiaohua Li, Yan Chen, Yue Zhang, Ying Liu, Yun Yun Gong, Xiang Qiu, Cui Ling Zhou, Yu Chen et al. · 2022 · Frontiers in Bioscience-Landmark
100. scHD4E: Novel ensemble learning-based differential expression analysis method for single-cell RNA-sequencing data
     Biplab Biswas, Nishith Kumar, Masahiro Sugimoto, Md. Aminul Hoque · 2024 · Computers in Biology and Medicine