Quantitative single-cell RNA-seq with unique molecular identifiers

Cited by (1,000)

Items 401–500 of 1,000

1. A computational method for estimating the PCR duplication rate in DNA and RNA-seq experiments
   Vikas Bansal · 2017 · BMC Bioinformatics
2. Bringing Renal Biopsy Interpretation Into the Molecular Age With Single-Cell RNA Sequencing
   Andrew F. Malone, Hao Wu, Benjamin D. Humphreys · 2017 · Seminars in Nephrology
3. Going the Distance: Optimizing RNA-Seq Strategies for Transcriptomic Analysis of Complex Viral Genomes
   Daniel Pearce Depledge, Ian Mohr, Angus C. Wilson · 2018 · Journal of Virology
4. Purification of Human CD34+CD90+ HSCs Reduces Target Cell Population and Improves Lentiviral Transduction for Gene Therapy
   Stefan Radtke, Dnyanada Pande, Margaret Cui, Anai M. Perez, Yan Yi Chan, Mark Enstrom, Stefanie Schmuck, Andrew Berger, Tom Eunson, Jennifer E. Adair et al. · 2020 · Molecular Therapy — Methods & Clinical Development
5. Exosome-based detection of EGFR T790M in plasma and pleural fluid of prospectively enrolled non-small cell lung cancer patients after first-line tyrosine kinase inhibitor therapy
   Yoonjung Kim, Saeam Shin, Kyung‐A Lee · 2021 · Cancer Cell International
6. Simulation-based benchmarking of isoform quantification in single-cell RNA-seq
   Jennifer Westoby, Marcela K. Sjöberg-Herrera, Anne C. Ferguson‐Smith, Martin Hemberg · 2018 · Genome biology
7. Incorporation of Unique Molecular Identifiers in TruSeq Adapters Improves the Accuracy of Quantitative Sequencing
   Jungeui Hong, David Gresham · 2017 · BioTechniques
8. Deciphering immune mechanisms in chronic inflammatory demyelinating polyneuropathies
   Jolien Wolbert, Mandy I. Cheng, Gerd Meyer zu Hörste, Maureen A. Su · 2020 · JCI Insight
9. Role of affinity in plasma cell development in the germinal center light zone
   Mohamed A. ElTanbouly, Víctor Ramos, Andrew J. MacLean, Spencer T. Chen, Maximilian Loewe, Sandra Steinbach, Tarek Ben Tanfous, Brianna A. Johnson, Melissa Cipolla, Anna Gazumyan et al. · 2023 · The Journal of Experimental Medicine
10. Single-Cell Genomic Analysis in Plants
    Yuxuan Yuan, HueyTyng Lee, Haifei Hu, Armin Scheben, David Edwards · 2018 · Genes
11. Tn5Prime, a Tn5 based 5′ capture method for single cell RNA-seq
    Charles Cole, Ashley Byrne, Anna E. Beaudin, E. Camilla Forsberg, Christopher Vollmers · 2018 · Nucleic Acids Research
12. UMI or not UMI, that is the question for scRNA-seq zero-inflation
    Yingying Cao, Simo Kitanovski, Ralf Küppers, Daniel E. Hoffmann · 2021 · Nature Biotechnology
13. Single Cell Analysis: From Technology to Biology and Medicine
    Xinghua Pan · 2014 · Single Cell Biology
14. NanoCAGE: A Method for the Analysis of Coding and Noncoding 5′-Capped Transcriptomes
    Stéphane Poulain, Sachi Kato, Ophélie Arnaud, Jean-Étienne R. L. Morlighem, Makoto Suzuki, Charles Plessy, Matthias Harbers · 2017 · Methods in molecular biology
15. Single‐cell RNA‐seq analysis reveals the platinum resistance gene COX7B and the surrogate marker CD63
    Nobuyuki Tanaka, Shintaro Katayama, A. K. Reddy, Kaneyasu Nishimura, Naoya Niwa, Hiroshi Hongo, Koichiro Ogihara, Takeo Kosaka, Ryuichi Mizuno, Eiji Kikuchi et al. · 2018 · Cancer Medicine
16. Optimization of fluorogenic RNA-based biosensors using droplet-based microfluidic ultrahigh-throughput screening
    Alexis Autour, Farah Bouhedda, Roger Cubí, Michaël Ryckelynck · 2019 · Methods
17. Single-cell gene expression profiling and cell state dynamics: collecting data, correlating data points and connecting the dots
    Carsten Marr, Joseph Zhou, Sui Huang · 2016 · Current Opinion in Biotechnology
18. Each cell counts: Hematopoiesis and immunity research in the era of single cell genomics
    Diego Adhemar Jaitin, Hadas Keren‐Shaul, Naama Elefant, Ido Amit · 2015 · Seminars in Immunology
19. A cost effective 5΄ selective single cell transcriptome profiling approach with improved UMI design
    Marie‐Jeanne Arguel, Kévin Lebrigand, Agnes C. Paquet, Sandra Ruiz García, Laure‐Emmanuelle Zaragosi, Pascal Barbry, Rainer Waldmann · 2016 · Nucleic Acids Research
20. LiBiNorm: an htseq-count analogue with improved normalisation of Smart-seq2 data and library preparation diagnostics
    Nigel P. Dyer, Vahid Shahrezaei, Daniel Hebenstreit · 2019 · PeerJ
21. Controlling for Confounding Effects in Single Cell RNA Sequencing Studies Using both Control and Target Genes
    Mengjie Chen, Xiang Zhou · 2017 · Scientific Reports
22. SpotSweeper: spatially aware quality control for spatial transcriptomics
    Michael S. Totty, Stephanie C. Hicks, Boyi Guo · 2025 · Nature Methods
23. Biased estimates of clonal evolution and subclonal heterogeneity can arise from PCR duplicates in deep sequencing experiments
    Erin N. Smith, Kristen Jepsen, Mahdieh Khosroheidari, Laura Z. Rassenti, Matteo D’Antonio, Emanuela M. Ghia, Dennis Anthony Carson, Catriona H. M. Jamieson, Thomas J. Kipps, Kelly A. Frazer · 2014 · Genome biology
24. Single-Cell Transcriptome Study as Big Data
    Pingjian Yu, Wei Lin · 2016 · Genomics Proteomics & Bioinformatics
25. Two-phase differential expression analysis for single cell RNA-seq
    Zhijin J. Wu, Yi Zhang, Michael L. Stitzel, Hao Wu · 2018 · Bioinformatics
26. Evaluating genetic causes of azoospermia: What can we learn from a complex cellular structure and single-cell transcriptomics of the human testis?
    Samuele Soraggi, Meritxell Riera, Ewa Rajpert‐De Meyts, Mikkel Heide Schierup, Kristian Almstrup · 2020 · Human Genetics
27. ATAC-seq with unique molecular identifiers improves quantification and footprinting
    Tao Zhu, Keyan Liao, Rongfang Zhou, Chunjiao Xia, Weibo Xie · 2020 · Communications Biology
28. Culturing the uncultured microbial majority in activated sludge: A critical review
    Yulin Zhang, Tong Zhang · 2022 · Critical Reviews in Environmental Science and Technology
29. UMI-tools: Modelling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy
    Tom S. Smith, Andreas Heger, Ian M. Sudbery · 2016 · bioRxiv (Cold Spring Harbor Laboratory)
30. DeepMetabolism: A Deep Learning System to Predict Phenotype from Genome Sequencing
    Weihua Guo, You (Eric) Xu, Xueyang Feng · 2017 · bioRxiv (Cold Spring Harbor Laboratory)
31. Single-cell and spatial transcriptomics: Advances in heart development and disease applications
    Xianglin Long, Xin Yuan, Jianlin Du · 2023 · Computational and Structural Biotechnology Journal
32. Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing
    Yi Xie, Huimei Chen, Vasuki Ranjani Chellamuthu, Ahmad bin Mohamed Lajam, Salvatore Albani, Andrea Hsiu Ling Low, Enrico G. Petretto, Jacques V. Behmoaras · 2024 · International Journal of Molecular Sciences
33. Noncoding RNAs in Polycomb and Trithorax Regulation: A Quantitative Perspective
    Leonie Ringrose · 2017 · Annual Review of Genetics
34. TAC-seq: targeted DNA and RNA sequencing for precise biomarker molecule counting
    Hindrek Teder, Mariann Koel, Priit Paluoja, Tatjana Jatsenko, Kadri Rekker, Triin Laisk, Viktorija Kukuškina, Agne Velthut‐Meikas, Olga Fjodorova, Maire Peters et al. · 2018 · npj Genomic Medicine
35. Single-Cell Transcriptome Data Clustering via Multinomial Modeling and Adaptive Fuzzy K-Means Algorithm
    Liang Chen, Weinan Wang, Yuyao Zhai, Minghua Deng · 2020 · Frontiers in Genetics
36. Quantile normalization of single-cell RNA-seq read counts without unique molecular identifiers
    F. William Townes, Rafael A. Irizarry · 2020 · Genome biology
37. Integrating transcriptomics and bulk time course data into a mathematical framework to describe and predict therapeutic resistance in cancer
    Kaitlyn E. Johnson, Grant R. Howard, Daylin Morgan, Eric A. Brenner, Andrea L. Gardner, R. Durrett, William Mo, Aziz M. Al’Khafaji, Eduardo D. Sontag, Angela M. Jarrett et al. · 2020 · Physical Biology
38. Quantitative Single-Cell Proteomics as a Tool to Characterize Cellular Hierarchies
    Erwin M. Schoof, Benjamin Furtwängler, Nil Üresin, Nicolas Rapin, Simonas Savickas, Coline Gentil, Eric R. Lechman, Ulrich auf dem Keller, John Edgar Dick, Bo Torben Porse · 2019 · bioRxiv (Cold Spring Harbor Laboratory)
39. PRISM: recovering cell-type-specific expression profiles from individual composite RNA-seq samples
    Antti Häkkinen, Kaiyang Zhang, Amjad Alkodsi, Noora Andersson, Erdoğan Pekcan Erkan, Jun Dai, Katja Kaipio, Tarja Lamminen, Naziha Mansuri, Kaisa Huhtinen et al. · 2021 · Bioinformatics
40. Gene expression variability in clonal populations: Causes and consequences
    Stefanie Roberfroid, Jos Vanderleyden, Hans P. L. Steenackers · 2016 · Critical Reviews in Microbiology
41. Comparative analysis of commercially available single-cell RNA sequencing platforms for their performance in complex human tissues
    Yue Julia Wang, Jonathan Schug, Jerome Lin, Zhiping Paul Wang, Andrew V. Kossenkov, Klaus H. Kaestner · 2019 · bioRxiv (Cold Spring Harbor Laboratory)
42. Endometriosis-associated infertility diagnosis based on saliva microRNA signatures
    Yohann Dabi, Stéphane Suisse, Anne Puchar, Léa Delbos, Mathieu Poilblanc, Philippe Descamps, Julie Haury, François Golfier, Ludmila Jornéa, Delphine Bouteiller et al. · 2022 · Reproductive BioMedicine Online
43. On the causes, consequences, and avoidance of PCR duplicates: Towards a theory of library complexity
    Nicolas C. Rochette, Angel G. Rivera‐Colón, Jessica Walsh, Thomas J. Sanger, Shane C. Campbell‐Staton, Julian Catchen · 2023 · Molecular Ecology Resources
44. A bead-based microfluidic approach to integrated single-cell gene expression analysis by quantitative RT-PCR
    Hao Ran Sun, Tim Olsen, Jing Zhu, Jianguo Tao, Brian Ponnaiya, Sally A. Amundson, David J. Brenner, Qiao Lin · 2014 · RSC Advances
45. Single-cell analyses of transcriptional heterogeneity in squamous cell carcinoma of urinary bladder
    Xiaolong Zhang, Meng Zhang, Yong Hou, Liqin Xu, Weidong Li, Zhihui Zou, Chunxiao Liu, Xun Xu, Song Wu · 2016 · Oncotarget
46. Single‐cell study of neural stem cells derived from human iPSCs reveals distinct progenitor populations with neurogenic and gliogenic potential
    Matti Lam, Tsukasa Sanosaka, Anders Lundin, Kent Imaizumi, Damla Etal, Fredrik H. Karlsson, Maryam Clausen, Jonathan Cairns, Ryan Hicks, Jun Kohyama et al. · 2019 · Genes to Cells
47. Embedding to reference t-SNE space addresses batch effects in single-cell classification
    Pavlin G. Poličar, Martin Stražar, Blaž Zupan · 2021 · Machine Learning
48. 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
49. MAUI‐seq: Metabarcoding using amplicons with unique molecular identifiers to improve error correction
    Bryden Fields, Sara Moeskjær, Ville‐Petri Friman, Stig Uggerhøj Andersen, J. Peter W. Young · 2020 · Molecular Ecology Resources
50. Single-cell analysis shows that adipose tissue of persons with both HIV and diabetes is enriched for clonal, cytotoxic, and CMV-specific CD4+ T cells
    Celestine N. Wanjalla, Wyatt J. McDonnell, Ramesh Ram, Abha Chopra, Rama Gangula, Shay Leary, Mona Mashayekhi, Joshua D. Simmons, Christian M. Warren, Samuel S. Bailin et al. · 2021 · Cell Reports Medicine
51. Large-scale translatome profiling annotates the functional genome and reveals the key role of genic 3′ untranslated regions in translatomic variation in plants
    Wanchao Zhu, Jing Xu, Sijia Chen, Jian Chen, Yan Liang, Cuijie Zhang, Qing Li, Jinsheng Lai, Lin Li · 2021 · Plant Communications
52. Revisiting hematopoiesis: applications of the bulk and single-cell transcriptomics dissecting transcriptional heterogeneity in hematopoietic stem cells
    Isha Monga, Karambir Kaur, Sandeep Kumar Dhanda · 2022 · Briefings in Functional Genomics
53. RNA sequencing: from tag-based profiling to resolving complete transcript structure
    Eleonora de Klerk, Johan T. den Dunnen, Peter A.C. ’t Hoen · 2014 · Cellular and Molecular Life Sciences
54. Revealing cellular and molecular complexity of the central nervous system using single cell sequencing
    Zhiwei Zeng, Nan Miao, Tao Sun · 2018 · Stem Cell Research & Therapy
55. An Overview of Single-Cell Isolation Techniques
    Qudsia Zeb, Ce Wang, Sarfraz Shafiq, Liangyu Liu · 2019 · Elsevier eBooks
56. Single-cell transcriptomics as a framework and roadmap for understanding the brain
    Mark S. Cembrowski · 2019 · Journal of Neuroscience Methods
57. Single-Cell RNA Sequencing Reveals the Migration of Osteoclasts in Giant Cell Tumor of Bone
    Wenyu Feng, Mingwei He, Xiaohong Jiang, Huijiang Liu, Tianyu Xie, Zhaojie Qin, Qian Huang, Shijie Liao, Chengsen Lin, Juliang He et al. · 2021 · Frontiers in Oncology
58. Differential expression of single‐cell RNA‐seq data using Tweedie models
    Himel Mallick, Suvo Chatterjee, Shrabanti Chowdhury, Saptarshi Chatterjee, Ali Rahnavard, Stephanie C. Hicks · 2022 · Statistics in Medicine
59. Single-cell transcriptome sequencing reveals heterogeneity of gastric cancer: progress and prospects
    Gaohua Deng, Xu Zhang, Yonglan Chen, Sicheng Liang, Sha Liu, Zehui Yu, Muhan Lü · 2023 · Frontiers in Oncology
60. 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
61. How deep is enough in single-cell RNA-seq?
    Aaron Streets, Yanyi Huang · 2014 · Nature Biotechnology
62. Global and targeted approaches to single-cell transcriptome characterization
    Aleksandra A. Kolodziejczyk, Tapio Lönnberg · 2017 · Briefings in Functional Genomics
63. Capturing the ‘ome’: the expanding molecular toolbox for RNA and DNA library construction
    Morgane Boone, Andries De Koker, Nico Callewaert · 2018 · Nucleic Acids Research
64. Centrosome aberrations and chromosome instability contribute to tumorigenesis and intra-tumor heterogeneity
    Shirley Jusino, Fabiola M. Fernández-Padín, Harold Ivan Saavedra · 2018 · Journal of Cancer Metastasis and Treatment
65. Single-cell transcriptome sequencing of rumen ciliates provides insight into their molecular adaptations to the anaerobic and carbohydrate-rich rumen microenvironment
    Jin-Mei Feng, Chuanqi Jiang, Zongyi Sun, Cong-Jie Hua, Jianfan Wen, Wei Miao, Jie Xiong · 2019 · Molecular Phylogenetics and Evolution
66. The Role of Single-Cell Technology in the Study and Control of Infectious Diseases
    Weikang Nicholas Lin, Matthew Zirui Tay, Ri Lu, Yi Liu, Chia‐Hung Chen, Lih Feng Cheow · 2020 · Cells
67. Orgo-Seq integrates single-cell and bulk transcriptomic data to identify cell type specific-driver genes associated with autism spectrum disorder
    Elaine T. Lim, Yingleong Chan, Pepper Dawes, Xiaoge Guo, Serkan Erdin, Derek J.C. Tai, Songlei Liu, Julia M. Reichert, Mannix J. Burns, Ying Chan et al. · 2022 · Nature Communications
68. From multitude to singularity: An up-to-date overview of scRNA-seq data generation and analysis
    Giulia Carangelo, Alberto Magi, Roberto Semeraro · 2022 · Frontiers in Genetics
69. IL-10 sensing by lung interstitial macrophages prevents bacterial dysbiosis-driven pulmonary inflammation and maintains immune homeostasis
    Seung Hyeon Kim, Zachary White, Anastasiia Gainullina, Soeun Kang, Jiseon Kim, Joseph Raul Dominguez, Yeonwoo Choi, Ivan Cabrera, Madison Plaster, Michihiro Takahama et al. · 2025 · Immunity
70. Assessing characteristics of RNA amplification methods for single cell RNA sequencing
    Hannah R. Dueck, Rizi Ai, Adrian Camarena, Bo Ding, Reymundo Dominguez, Oleg Vadimovich Evgrafov, Jian‐Bing Fan, Stephen A. Fisher, Jennifer S. Herstein, Tae Kyung Kim et al. · 2016 · BMC Genomics
71. The efficacy and further functional advantages of random-base molecular barcodes for absolute and digital quantification of nucleic acid molecules
    Taisaku Ogawa, Kirill A. Kryukov, Tadashi Imanishi, Katsuyuki Shiroguchi · 2017 · Scientific Reports
72. A microfluidic platform towards automated multiplexed in situ sequencing
    Nicolas Maïno, Thomas Hauling, Giulia Cappi, Narayanan Madaboosi, Diego Dupouy, Mats F. Nilsson · 2019 · Scientific Reports
73. Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes
    Chuan Ku, Arnau Sebé-Pedrós · 2019 · Philosophical Transactions of the Royal Society B Biological Sciences
74. Molecular tracking devices quantify antigen distribution and archiving in the murine lymph node
    Walsh, Shannon M, Sheridan, Ryan M, Lucas, Erin D, Doan, Thu A, Ware, Brian C, Schafer, Johnathon, Fu, Rui, Burchill, Matthew A, Hesselberth, Jay R, Tamburini, Beth Ann Jiron · 2021 · eLife
75. scruff: an R/Bioconductor package for preprocessing single-cell RNA-sequencing data
    Zhe Wang, Junming Hu, William Evan Johnson, Joshua David Campbell · 2019 · BMC Bioinformatics
76. Elucidating the cellular dynamics of the brain with single-cell RNA sequencing
    Aida Cardona‐Alberich, Manon Tourbez, Sarah F. Pearce, Christopher R. Sibley · 2021 · RNA Biology
77. Microfluidics Facilitates the Development of Single-Cell RNA Sequencing
    Yating Pan, Wenjian Cao, Ying Mu, Qiangyuan Zhu · 2022 · Biosensors
78. The Application of Single-Cell RNA Sequencing in the Inflammatory Tumor Microenvironment
    Jiayi Zhao, Yiwei Shi, Guangwen Cao · 2023 · Biomolecules
79. Q-RRBS: a quantitative reduced representation bisulfite sequencing method for single-cell methylome analyses
    Kangli Wang, Xianfeng Li, Shanshan Dong, Jialong Liang, Fengbiao Mao, Cheng Zeng, Honghu Wu, Jinyu Wu, Wanshi Cai, Zhong Sheng Sun · 2015 · Epigenetics
80. Implications of Epigenetic Variability within a Cell Population for “Cell Type” Classification
    Inna Tabansky, Joel N. H. Stern, Donald W. Pfaff · 2015 · Frontiers in Behavioral Neuroscience
81. Single cell sequencing approaches for complex biological systems
    Timour Baslan, James B Hicks · 2014 · Current Opinion in Genetics & Development
82. Digital Encoding of Cellular mRNAs Enabling Precise and Absolute Gene Expression Measurement by Single-Molecule Counting
    Glenn K. Fu, Julie Wilhelmy, David Stern, H. Christina Fan, Stephen P. A. Fodor · 2014 · Analytical Chemistry
83. Modeling Enzyme Processivity Reveals that RNA-Seq Libraries Are Biased in Characteristic and Correctable Ways
    Nathan Archer, Mark D. Walsh, Vahid Shahrezaei, Daniel Hebenstreit · 2016 · Cell Systems
84. Single cell transcriptome sequencing: A new approach for the study of mammalian sex determination
    Isabelle Stévant, Serge Nef · 2018 · Molecular and Cellular Endocrinology
85. scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data
    Ruoxin Li, Gerald Quon · 2019 · Genome biology
86. Emerging deep learning methods for single‐cell RNA‐seq data analysis
    Jie Zheng, Ke Wang · 2019 · Quantitative Biology
87. Redefining intestinal immunity with single-cell transcriptomics
    Kylie Renee James, Rasa Elmentaite, Sarah Amalia Teichmann, Georgina Louise Hold · 2021 · Mucosal Immunology
88. Lung Cell Atlases in Health and Disease
    Taylor Sterling Adams, Arnaud Marlier, Naftali Kaminski · 2022 · Annual Review of Physiology
89. Cellular Deconstruction: Finding Meaning in Individual Cell Variation
    James H. Eberwine, Junhyong Kim · 2015 · Trends in Cell Biology
90. Microfluidics: A new tool for microbial single cell analyses in human microbiome studies
    Yuguang Liu, Marina R. S. Walther-Antonio · 2017 · Biomicrofluidics
91. Methods and challenges in the analysis of single-cell RNA-sequencing data
    Pablo G. Cámara · 2017 · Current Opinion in Systems Biology
92. Primary cilia promote the differentiation of human neurons through the WNT signaling pathway
    Coschiera, Andrea, Yoshihara, Masahito, Lauter, Gilbert, Ezer, Sini, Pucci, Mariangela, Li, Haonan, Kavšek, Alan, Riedel, Christian G., Kere, Juha, Swoboda, Peter · 2024 · BMC Biology
93. Alternative TSSs are co‐regulated in single cells in the mouse brain
    Karlsson, Kasper, Lönnerberg, Peter, Linnarsson, Sten · 2017 · Molecular Systems Biology
94. Single-cell transcriptomics: background, technologies, applications, and challenges
    Lucky Duhan, Deepika Kumari, Mohammad Naime, Virinder Singh Parmar, Anil Kumar Chhillar, Mehak Dangi, Ritu Pasrija · 2024 · Molecular Biology Reports
95. Stoichiometric constraints for detection of EV‐borne biomarkers in blood
    Nataša Zarovni, Danilo Mladenović, Dario Brambilla, Federica Panico, Marcella Chiari · 2025 · Journal of Extracellular Vesicles
96. Exploring viral infection using single-cell sequencing
    Sylvie Rato, Monica Golumbeanu, Amalio Telenti, Angela Ciuffi · 2016 · Virus Research
97. Comparative cell cycle transcriptomics reveals synchronization of developmental transcription factor networks in cancer cells
    Johan Boström, Zuzana Šramková, Alena Salašová, Helena A. D. Johard, Diana Mahdessian, Radek Fedr, Carolyn A. Marks, Jiřina Medalová, Karel Souček, Emma K. Lundberg et al. · 2017 · PLoS ONE
98. CellFishing.jl: an ultrafast and scalable cell search method for single-cell RNA sequencing
    Kenta Sato, Koki Tsuyuzaki, Kentaro Shimizu, Itoshi Nikaido · 2019 · Genome biology
99. Single-Cell Sequencing in Precision Medicine
    Julia Erin Wiedmeier, Pawan Noel, Wei Lin, Daniel D. Von Hoff, Haiyong Han · 2019 · Cancer treatment and research
100. New era of trophoblast research: integrating morphological and molecular approaches
     Shingo Io, Eiji Kondoh, Yoshitsugu Chigusa, Kaoru Kawasaki, Masaki Mandai, and Shigehito Yamada · 2020 · Human Reproduction Update