The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation
Open accessAbstract
Key Points: An expression map of HSPC differentiation from single-cell RNA sequencing of HSPCs provides insights into blood stem cell differentiation. A user-friendly Web resource provides access to single-cell gene expression profiles for the wider research community.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“But recent state maps from scSeq (9), as well as clonal studies using barcodes (10) and single cell culture (11), suggest that the traditional intermediate cell types are internally heterogeneous in state and fate potential, with HSPCs lying along a continuum of states rather than a stepwise hierarchy.”
From Lineage tracing on transcriptional landscapes links state to fate during differentiation (2020) · cites this paper as [9]
In the citing paper
“When computationally reconstructed, single-cell RNA sequencing (scRNA-seq) profiling of the mammalian hematopoietic system typically produces a largely continuous distribution of cells from the earliest HSCs through the characteristic hematopoietic lineages (Nestorowa et al., 2016; Olsson et al., 2016; Paul et al., 2015; Pellin et al., 2019; Tusi et al., 2018; Weinreb et al., 2020).”
From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Nestorowa et al., 2016
In the citing paper
“As part of the genomics revolution, increasingly accurate deep sequencing and novel methods of cell tracking have revealed hematopoiesis to be more of a continuous and less of a discrete and punctuated process than originally envisioned.”
From Unraveling Hematopoiesis through the Lens of Genomics (2020) · cites this paper as Nestorowa et al., 2016
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
HTSeq—a Python framework to work with high-throughput sequencing data
Anders, S., Pyl, P. T., & Huber, W. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btu638 · Cited by 21,464
Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool
Chen, E. Y., Tan, C. M., Kou, Y., Duan, Q., Wang, Z., Meirelles, G. V., Clark, N. R., & Ma’ayan, A. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-128 · Cited by 7,814
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314
Full-length RNA-seq from single cells using Smart-seq2
Picelli, S., Faridani, O. R., Björklund, Å. K., Winberg, G., Sagasser, S., & Sandberg, R. (2014) · Nature Protocols · doi:10.1038/nprot.2014.006 · Cited by 4,137
Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells
Klein, A. M., Mazutis, L., Akartuna, I., Tallapragada, N., Veres, A., Li, V., Peshkin, L., Weitz, D. A., & Kirschner, M. W. (2015) · Cell · doi:10.1016/j.cell.2015.04.044 · Cited by 3,356
Kiel, M. J., Yilmaz, Ö. H., Iwashita, T., Yilmaz, O. H., Terhorst, C., & Morrison, S. J. (2005) · Cell · doi:10.1016/j.cell.2005.05.026 · Cited by 3,168
A clonogenic common myeloid progenitor that gives rise to all myeloid lineages
Akashi, K., Traver, D., Miyamoto, T., & Weissman, I. L. (2000) · Nature · doi:10.1038/35004599 · Cited by 2,617
Wilson, A., Laurenti, E., Oser, G., van der Wath, R. C., Blanco-Bose, W., Jaworski, M., Offner, S., Dunant, C. F., Eshkind, L., Bockamp, E., et al. (2008) · Cell · doi:10.1016/j.cell.2008.10.048 · Cited by 1,908
Self-citationFast and SNP-tolerant detection of complex variants and splicing in short reads
Wu, T. D., & Nacu, S. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq057 · Cited by 1,894
Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types
Jaitin, D. A., Kenigsberg, E., Keren-Shaul, H., Elefant, N., Paul, F., Zaretsky, I., Mildner, A., Cohen, N., Jung, S., Tanay, A., et al. (2014) · Science · doi:10.1126/science.1247651 · Cited by 1,795
Cited by
Sorted by citations
Items 201–300 of 751
Clonal multi-omics reveals Bcor as a negative regulator of emergency dendritic cell development
Tian, L., Tomei, S., Schreuder, J., Weber, T., Amann‐Zalcenstein, D., Lin, D. S. Y., Tran, J., Audiger, C., Chu, M., Jarratt, A., et al. (2021) · Immunity · doi:10.1016/j.immuni.2021.03.012 · Cited by 39
Lee, D. R., Rhodes, C. T., Mitra, A., Zhang, Y., Maric, D., Dale, R. K., & Petros, T. J. (2022) · eLife · doi:10.7554/elife.71864 · Cited by 41
Li, H., Natarajan, A., Ezike, J., Barrasa, M. I., Le, Y., Feder, Z. A., Yang, H., Ma, C., Markoulaki, S., & Lodish, H. F. (2019) · Developmental Cell · doi:10.1016/j.devcel.2019.01.026 · Cited by 41
Accounting for cell type hierarchy in evaluating single cell RNA-seq clustering
Wu, Z. J., & Wu, H. (2020) · Genome biology · doi:10.1186/s13059-020-02027-x · Cited by 41
Li, J., Williams, M., Park, H. J., Bastos, H. P., Wang, X., Prins, D., Wilson, N. K., Johnson, C., Sham, K., Wantoch, M., et al. (2022) · Blood · doi:10.1182/blood.2021014009 · Cited by 39
Self-citationBRD9 determines the cell fate of hematopoietic stem cells by regulating chromatin state
Xiao, M., Kondo, S., Nomura, M., Kato, S., Nishimura, K., Zang, W., Zhang, Y., Akashi, T., Viny, A. D., Shigehiro, T., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-44081-6 · Cited by 39
Li, S., Liu, Y., Shen, L.-C., He, Y., Song, J., & Yu, D. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad529 · Cited by 36
Loughran, S. J., Haas, S. F., Wilkinson, A. C., Klein, A. M., & Brand, M. (2020) · Experimental Hematology · doi:10.1016/j.exphem.2020.07.002 · Cited by 40
Single-cell RNA sequencing to track novel perspectives in HSC heterogeneity
Zhang, P., Li, X., Pan, C., Zheng, X., Hu, B., Xie, R., Hu, J., Shang, X., & Yang, H. (2022) · Stem Cell Research & Therapy · doi:10.1186/s13287-022-02718-1 · Cited by 44
Cloning a profibrotic stem cell variant in idiopathic pulmonary fibrosis
Wang, S., Rao, W. H., Hoffman, A., Lin, J. M., Li, J., Lin, T., Liew, A.-A., Vincent, M., Mertens, T. C. J., Karmouty‐Quintana, H., et al. (2023) · Science Translational Medicine · doi:10.1126/scitranslmed.abp9528 · Cited by 35
D’Antonio, M., Nguyen, J., Arthur, T. D., Matsui, H., Donovan, M. K. R., D’Antonio‐Chronowska, A., & Frazer, K. A. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009918 · Cited by 37
Qu, R., Gupta, K., Dong, D., Jiang, Y., Landa, B., Saez, C., Strickland, G., Levinsohn, J. L., Weng, P., Taketo, M. M., et al. (2022) · Developmental Cell · doi:10.1016/j.devcel.2022.03.011 · Cited by 36
Transplanting rejuvenated blood stem cells extends lifespan of aged immunocompromised mice
Montserrat‐Vazquez, S., Ali, N., Matteini, F., Lozano-Bartolomé, J., Tu, Z., Mejía-Ramírez, E., Marka, G., Vollmer, A., Soller, K., Saçma, M., et al. (2022) · npj Regenerative Medicine · doi:10.1038/s41536-022-00275-y · Cited by 38
Identification of a physiologic vasculogenic fibroblast state to achieve tissue repair
Pal, D., Ghatak, S., Singh, K., Abouhashem, A. S., Kumar, M., Masry, M. S. E., Mohanty, S. K., Palakurti, R., Rustagi, Y., Tabasum, S., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-36665-z · Cited by 35
CD62L expression level determines the cell fate of myeloid progenitors
Ito, Y., Nakahara, F., Kagoya, Y., & Kurokawa, M. (2021) · Stem Cell Reports · doi:10.1016/j.stemcr.2021.10.012 · Cited by 36
Mitochondria in innate immunity signaling and its therapeutic implications in autoimmune diseases
Jiao, Y., Yan, Z., & Yang, A. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1160035 · Cited by 35
Yang, Y., Li, G., Qian, H., Wilhelmsen, K. C., Shen, Y., & Li, Y. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa097 · Cited by 34
Amann‐Zalcenstein, D., Tian, L., Schreuder, J., Tomei, S., Lin, D. S. Y., Fairfax, K. A., Bolden, J. E., McKenzie, M. D., Jarratt, A., Hilton, A. A., et al. (2020) · Nature Immunology · doi:10.1038/s41590-020-0799-x · Cited by 35
DRscDB: A single-cell RNA-seq resource for data mining and data comparison across species
Hu, Y., Tattikota, S. G., Liu, Y., Comjean, A., Gao, Y., Forman, C., Kim, G. S., Rodiger, J., Papatheodorou, I., dos Santos, G., et al. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.04.021 · Cited by 34
Martell, D. J., Merens, H. E., Caulier, A., Fiorini, C., Ulirsch, J. C., Ietswaart, R., Choquet, K., Graziadei, G., Brancaleoni, V., Cappellini, M. D., et al. (2023) · Developmental Cell · doi:10.1016/j.devcel.2023.07.018 · Cited by 36
Monga, I., Kaur, K., & Dhanda, S. K. (2022) · Briefings in Functional Genomics · doi:10.1093/bfgp/elac002 · Cited by 40
Wang, Y.-C., Cao, Y., Pan, C., Zhou, Z., Yang, L., & Lusis, A. J. (2023) · The Journal of Experimental Medicine · doi:10.1084/jem.20221437 · Cited by 33
Cui, L., Moraga, I., Lerbs, T., Neste, C. V., Wilmes, S., Tsutsumi, N., Trotman-Grant, A. C., Gakovic, M., Andrews, S., Gotlib, J. R., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2017849118 · Cited by 32
A data-driven clustering recommendation method for single-cell RNA-sequencing data
Tian, Y., Zheng, R., Liang, Z., Li, S., Wu, F., & Li, M. (2021) · Tsinghua Science & Technology · doi:10.26599/tst.2020.9010028 · Cited by 33
Tfap2b specifies an embryonic melanocyte stem cell that retains adult multifate potential
Brombin, A., Simpson, D. J., Trávníčková, J., Brunsdon, H., Zeng, Z., Lu, Y., Young, A. I. J., Chandra, T., & Patton, E. E. (2022) · Cell Reports · doi:10.1016/j.celrep.2021.110234 · Cited by 33
Sinha, S., Dwivedi, T. R., Yengkhom, R., Bheemsetty, V. A., Abe, T., Kiyonari, H., VijayRaghavan, K., & Inamdar, M. S. (2019) · Blood · doi:10.1182/blood.2019000530 · Cited by 32
Environmental exposures, stem cells, and cancer
Thong, T., Forté, C. A., Hill, E. M., & Colacino, J. A. (2019) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2019.107398 · Cited by 32
Song, F., Chan, G. M. A., & Wei, Y. (2020) · Nature Communications · doi:10.1038/s41467-020-16905-2 · Cited by 31
netSmooth: Network-smoothing based imputation for single cell RNA-seq
Ronen, J., & Akalin, A. (2018) · F1000Research · doi:10.12688/f1000research.13511.1 · Cited by 31
Adapting systems biology to address the complexity of human disease in the single-cell era
Fischer, D. S., Villanueva, M. A., Winter, P. S., & Shalek, A. K. (2025) · Nature Reviews Genetics · doi:10.1038/s41576-025-00821-6 · Cited by 32
Borcherding, N. C., Severson, K. J., Henderson, N., Ortolan, L. D. S., Rosenthal, A. C., Bellizzi, A. M., Liu, V., Link, B. K., Mangold, A. R., & Jabbari, A. (2022) · Blood Advances · doi:10.1182/bloodadvances.2021005991 · Cited by 30
ABC portal: a single-cell database and web server for blood cells
Gao, X., Hong, F., Hu, Z., Zhang, Z., Yang, L., Li, X., & Cheng, T. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac646 · Cited by 32
Towards reliable quantification of cell state velocities
Marot-Lassauzaie, V., Bouman, B. J., Donaghy, F. D., Demerdash, Y., Essers, M. A. G., & Haghverdi, L. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010031 · Cited by 30
Zhang, B., Zhao, D., Chen, F., Frankhouser, D. E., Wang, H., Pathak, K. V., Dong, L., Torres, A., Garcia‐Mansfield, K., Zhang, Y., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-41167-z · Cited by 30
Kinalis, S., Nielsen, F. C., Winther, O., & Bagger, F. O. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-2952-9 · Cited by 29
Wang, R., Peng, L., Xiao, Y., Zhou, Q., Wang, Z., Tang, L., Xiao, H., Yang, K., Liu, H., & Li, L. (2023) · Cancer Gene Therapy · doi:10.1038/s41417-022-00582-y · Cited by 29
S100A6 is a critical regulator of hematopoietic stem cells
Grahn, T. H. M., Niroula, A., Végvári, Á., Oburoglu, L., Pertesi, M., Warsi, S., Safi, F., Miharada, N., Capellera-Garcia, S., Siva, K., et al. (2020) · Leukemia · doi:10.1038/s41375-020-0901-2 · Cited by 29
A mechanistic model for the negative binomial distribution of single-cell mRNA countsPreprint
Amrhein, L., Harsha, K., & Fuchs, C. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/657619 · Cited by 32
Yang, X. H., Goldstein, A., Sun, Y., Wang, Z., Wei, M., Moskowitz, I. P. G., & Cunningham, J. M. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac452 · Cited by 28
Role of YAP as a Mechanosensing Molecule in Stem Cells and Stem Cell-Derived Hematopoietic Cells
Damkham, N., Issaragrisil, S., & Lorthongpanich, C. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232314634 · Cited by 28
tRNA m1A modification regulate HSC maintenance and self-renewal via mTORC1 signaling
Zuo, H., Wu, A., Wang, M., Hong, L., & Wang, H. (2024) · Nature Communications · doi:10.1038/s41467-024-50110-9 · Cited by 28
Li, R., & Quon, G. (2019) · Genome biology · doi:10.1186/s13059-019-1806-0 · Cited by 30
Kuciński, I., Wilson, N. K., Hannah, R., Kinston, S., Cauchy, P., Lenaerts, A., Grosschedl, R., & Göttgens, B. (2020) · The EMBO Journal · doi:10.15252/embj.2020104983 · Cited by 29
Self-citationPrins, D., Park, H. J., Watcham, S., Li, J., Vacca, M., Bastos, H. P., Gerbaulet, A., Vidal‐Puig, A., Göttgens, B., & Green, A. R. (2020) · Science Advances · doi:10.1126/sciadv.abd3139 · Cited by 30
Self-citationCellexalVR: A virtual reality platform to visualize and analyze single-cell omics data
Legetth, O., Rodhe, J., Lang, S., Dhapola, P., Wallergård, M., & Soneji, S. (2021) · iScience · doi:10.1016/j.isci.2021.103251 · Cited by 31
Dysregulation of haematopoietic stem cell regulatory programs in acute myeloid leukaemia
Basilico, S., & Göttgens, B. (2017) · Journal of Molecular Medicine · doi:10.1007/s00109-017-1535-3 · Cited by 30
Self-citationFundamental limits on dynamic inference from single cell snapshots
Weinreb, C., Wolock, S., Tusi, B. K., Socolovsky, M., & Klein, A. M. (2017) · doi:10.1101/170118 · Cited by 27
Kim, I. S., Wu, J., Rahme, G. J., Battaglia, S., Dixit, A. C., Gaskell, E., Chen, H., Pinello, L., & Bernstein, B. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108222 · Cited by 27
Triku: a feature selection method based on nearest neighbors for single-cell data
Ascensión, A. M., Ibáñez-Solé, O., Inza, I., Izeta, A., & Araúzo-Bravo, M. J. (2022) · GigaScience · doi:10.1093/gigascience/giac017 · Cited by 28
Embryonic Origins of the Hematopoietic System: Hierarchies and Heterogeneity
Vink, C. S., Mariani, S. A., & Dzierzak, E. A. (2022) · HemaSphere · doi:10.1097/hs9.0000000000000737 · Cited by 27
Wang, P., Xiao, W., Li, H., Peng, L., Li, S., Lei, Y., Shu, H., Gao, L., Zhao, D. Y., & Zeng, J. (2023) · Nature Communications · doi:10.1038/s41467-023-44103-3 · Cited by 29
Cell lineage inference from SNP and scRNA-Seq data
Ding, J., Lin, C. H., & Bar‐Joseph, Z. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz146 · Cited by 27
Chen, T., Zhou, Z., Liu, Y., Xu, J., Zhu, C., Sun, R., Hu, H., Liu, Y., Dai, L., Holmdahl, R., et al. (2024) · Redox Biology · doi:10.1016/j.redox.2024.103401 · Cited by 26
della Volpe, L., Midena, F., Vacca, R., Tavella, T., Alessandrini, L., Farina, G., Brandas, C., Furno, E. L., Giannetti, K., Carsana, E., et al. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101823 · Cited by 28
Barbarani, G., Fugazza, C., Strouboulis, J., & Ronchi, A. E. (2019) · Frontiers in Physiology · doi:10.3389/fphys.2019.00091 · Cited by 26
Gene Regulatory Network Inference using 3D Convolutional Neural Network
Fan, Y. B., & Ma, X. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i1.16082 · Cited by 26
DDX41 is needed for pre- and postnatal hematopoietic stem cell differentiation in mice
Ma, J., Mahmud, N., Bosland, M. C., & Ross, S. R. (2022) · Stem Cell Reports · doi:10.1016/j.stemcr.2022.02.010 · Cited by 26
Combining single-cell tracking and omics improves blood stem cell fate regulator identification
Wehling, A., Loeffler, D., Zhang, Y., Kull, T., Donato, C., Szczerba, B. M., Ortega, G. C., Lee, M., Moor, A. E., Göttgens, B., et al. (2022) · Blood · doi:10.1182/blood.2022016880 · Cited by 27
Self-citationVégh, P., & Haniffa, M. A. (2018) · Briefings in Functional Genomics · doi:10.1093/bfgp/ely003 · Cited by 28
Tracking the origin, development, and differentiation of hematopoietic stem cells
Dharampuriya, P. R., Scapin, G., Wong, C., Wagner, K., Cillis, J. L., & Shah, D. I. (2017) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2018.01.002 · Cited by 26
Huang, X., Li, X., Qin, P., Zhu, Y., Xu, S., & Chen, J. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00582 · Cited by 27
Wang, W., Tan, H., Sun, M., Han, Y., Chen, W., Qiu, S., Zheng, K., Wei, G., & Ni, T. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab089 · Cited by 27
Ambrosi, T. H., Taheri, S., Chen, K., Sinha, R., Wang, Y., Hunt, E. J., Goodnough, L. H., Murphy, M. P., Steininger, H. M., Hoover, M. Y., et al. (2025) · Cell stem cell · doi:10.1016/j.stem.2025.02.013 · Cited by 27
van den Berk, P. C. M., Lancini, C., Serresi, M., Sánchez-Bailón, M. P., Hulsman, D., Pritchard, C., Song, J., Schmitt, M. J., Tanger, E., Popp, O., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108533 · Cited by 25
Reliance on Cox10 and oxidative metabolism for antigen-specific NK cell expansion
Mah-Som, A. Y., Keppel, M. P., Tobin, J. M., Kolicheski, A., Saucier, N., Sexl, V., French, A. R., Wagner, J. A., Fehniger, T. A., & Cooper, M. A. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109209 · Cited by 27
ResPAN: a powerful batch correction model for scRNA-seq data through residual adversarial networks
Wang, Y., Liu, T., & Zhao, H. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac427 · Cited by 25
DRAG in situ barcoding reveals an increased number of HSPCs contributing to myelopoiesis with age
Urbanus, J. H. M., Cosgrove, J., Beltman, J. B., Elhanati, Y., Moral, R. D. A., Conrad, C., van Heijst, J. W. J., Tubeuf, E., Velds, A., Kok, L., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-37167-8 · Cited by 25
Acan downregulation in parvalbumin GABAergic cells reduces spontaneous recovery of fear memories
Lavertu-Jolin, M., Chattopadhyaya, B., Chehrazi, P., Carrier, D., Wünnemann, F., Leclerc, S., Dumouchel, F., Robertson, D. N., Affia, H., Saba, K., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02085-0 · Cited by 27
Lei, Q., Xiang, K., Cheng, L. Z., & Xiang, M. (2023) · Stem Cell Reports · doi:10.1016/j.stemcr.2023.11.004 · Cited by 25
Modeling the Hematopoietic Landscape
Brown, G., & Ceredig, R. (2019) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2019.00104 · Cited by 27
Heydari, T., Langley, M. A., Fisher, C. L., Aguilar‐Hidalgo, D., Shukla, S., Yachie‐Kinoshita, A., Hughes, M. R., McNagny, K. M., & Zandstra, P. W. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009907 · Cited by 26
Eosinophil innate immune memory after bacterial skin infection promotes allergic lung inflammation
Radhouani, M., Farhat, A., Hakobyan, A., Zahalka, S., Pimenov, L., Fokina, A., Hladik, A., Lakovits, K., Brösamlen, J., Dvorak, V., et al. (2025) · Science Immunology · doi:10.1126/sciimmunol.adp6231 · Cited by 25
Fang, D., Tan, X.-H., Song, W., Gu, Y., Pan, J., Yang, X., Song, W., Yuan, Y.-M., Peng, J., Zhang, Z., et al. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.874915 · Cited by 24
Lin, Z., & Ou-Yang, L. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac586 · Cited by 24
Learning time-varying information flow from single-cell epithelial to mesenchymal transition data
Krishnaswamy, S., Zivanovic, N., Sharma, R., Pe’er, D., & Bodenmiller, B. (2018) · PLoS ONE · doi:10.1371/journal.pone.0203389 · Cited by 25
Hematopoietic stem cells retain functional potential and molecular identity in hibernation cultures
Oedekoven, C. A., Belmonte, M., Bode, D., Hamey, F., Shepherd, M. S., Che, J. L. C., Boyd, G., McDonald, C., Belluschi, S., Diamanti, E., et al. (2021) · Stem Cell Reports · doi:10.1016/j.stemcr.2021.04.002 · Cited by 24
Self-citationCalabrese, D. R., Ekstrand, C. A., Yellamilli, S., Singer, J. P., Hays, S. R., Leard, L. E., Shah, R., Venado, A. E., Kolaitis, N. A., Perez, A. A., et al. (2024) · The Journal of Heart and Lung Transplantation · doi:10.1016/j.healun.2024.02.007 · Cited by 23
Wang, J., Chen, Y., & Zou, Q. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3412753 · Cited by 27
Identification of hematopoietic stem cells residing in the meninges of adult mice at steady state
Niu, C., Yu, J., Zou, T., Lu, Y., Deng, L., Yun, H., Si, C.-Y., Wu, X., Jiang, H., Guo, T., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111592 · Cited by 23
Linke, F., Johnson, J. E. C., Kern, S., Bennett, C., Lourdusamy, A., Lea, D., Clifford, S. C., Merry, C. L. R., Stolnik, S., Alexander, M. R., et al. (2023) · Acta Neuropathologica Communications · doi:10.1186/s40478-022-01496-4 · Cited by 25
Impact of DNA methylation programming on normal and pre-leukemic hematopoiesis
Langstein, J., Milsom, M. D., & Lipka, D. B. (2017) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2017.09.008 · Cited by 25
Linked optical and gene expression profiling of single cells at high-throughput
Zhang, J. Q., Siltanen, C. A., Liu, L., Chang, K., Gartner, Z. J., & Abate, A. R. (2020) · Genome biology · doi:10.1186/s13059-020-01958-9 · Cited by 25
Shin, W., Su, Z., Yi, S. S., & Kim, H. J. (2022) · iScience · doi:10.1016/j.isci.2022.105521 · Cited by 22
Wang, Z., Li, Z., Luan, T., Cui, G., Shu, S., Liang, Y., Zhang, K., Xiao, J., Yu, W., Cui, J., et al. (2024) · Developmental Cell · doi:10.1016/j.devcel.2024.06.016 · Cited by 22
Kaur, S., Sehgal, A., Wu, A., Millard, S. M., Batoon, L., Sandrock, C. J., Ferrari-Cestari, M., Lévesque, J.-P., Hume, D. A., Raggatt, L. J., et al. (2021) · Journal of Hematology & Oncology · doi:10.1186/s13045-020-00997-w · Cited by 24
Effect of imputation on gene network reconstruction from single-cell RNA-seq data
Ly, L.-H., & Vingron, M. (2021) · Patterns · doi:10.1016/j.patter.2021.100414 · Cited by 24
EBF1 primes B-lymphoid enhancers and limits the myeloid bias in murine multipotent progenitors
Lenaerts, A., Kuciński, I., Deboutte, W., Derecka, M., Cauchy, P., Manke, T., Göttgens, B., & Grosschedl, R. (2022) · The Journal of Experimental Medicine · doi:10.1084/jem.20212437 · Cited by 24
Self-citationData mining for mutation-specific targets in acute myeloid leukemia
Benard, B. A., Gentles, A. J., Köhnke, T., Majeti, R., & Thomas, D. (2019) · Leukemia · doi:10.1038/s41375-019-0387-y · Cited by 23
Single-cell transcriptional uncertainty landscape of cell differentiation
Gao, N. P., Gandrillon, O., Páldi, A., Herbach, U., & Gunawan, R. (2023) · F1000Research · doi:10.12688/f1000research.131861.1 · Cited by 25
Bisht, K., Brunck, M. E. G., Matsumoto, T., McGirr, C., Nowlan, B., Fleming, W., Keech, T., Magor, G. W., Perkins, A. C., Davies, J. M., et al. (2019) · Blood Advances · doi:10.1182/bloodadvances.2018017566 · Cited by 20
Yang, Y., Li, G., Xie, Y., Wang, L., Lagler, T. M., Yang, Y., Liu, J., Li, Q., & Li, Y. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab122 · Cited by 21
singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality
Stein, D. F., Chen, H., Vinyard, M. E., Qin, Q., Combs, R. D., Zhang, Q., & Pinello, L. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.764170 · Cited by 22
Induction of Rosette-to-Lumen stage embryoids using reprogramming paradigms in ESCs
Langkabel, J., Horne, A., Bonaguro, L., Holsten, L., Hesse, T., Knaus, A., Riedel, Y. L., Becker, M., Händler, K., Elmzzahi, T., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-27586-w · Cited by 21
Macrophage response mediated by extracellular matrix: recent progress
Xiao, W., Yang, Y., Chu, C., Rung, S., Wang, Z., Man, Y., Lin, J., & Qu, Y. (2022) · Biomedical Materials · doi:10.1088/1748-605x/aca946 · Cited by 21
Okuda, S., Ohuchida, K., Nakamura, S., Tsutsumi, C., Hisano, K., Mochida, Y., Kawata, J., Ohtsubo, Y., Shinkawa, T., Iwamoto, C., et al. (2023) · iScience · doi:10.1016/j.isci.2023.106480 · Cited by 21
A track of the clones: new developments in cellular barcoding
Lyne, A.-M., Kent, D. G., Laurenti, E., Cornils, K., Glauche, I., & Perié, L. (2018) · Experimental Hematology · doi:10.1016/j.exphem.2018.11.005 · Cited by 21
Self-citationLei, J. (2020) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2020.110196 · Cited by 23
Symmetric and asymmetric activation of hematopoietic stem cells
Loeffler, D., & Schroeder, T. (2021) · Current Opinion in Hematology · doi:10.1097/moh.0000000000000644 · Cited by 24
Hematopoietic Stem Cells Self-Renew Symmetrically or Gradually Proceed to DifferentiationPreprint
Barile, M., Busch, K., Fanti, A.-K., Greco, A., Wang, X., Oguro, H., Zhang, Q., Morrison, S. J., Rodewald, H.-R., & Höfer, T. (2020) · SSRN Electronic Journal · doi:10.1101/2020.08.06.239186 · Cited by 24
New frameworks for hematopoiesis derived from single-cell genomics
Safina, K. R., & van Galen, P. (2024) · Blood · doi:10.1182/blood.2024024006 · Cited by 23
Metadata
- Authors
- Nestorowa, S., Hamey, F. K., Pijuan Sala, B., Diamanti, E., Shepherd, M., Laurenti, E., Wilson, N. K., Kent, D. G., & Göttgens, B.
- Affiliations
- Wellcome/MRC Cambridge Stem Cell Institute (GB)
- Department of Haematology and Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom
- ORCID
- Venue
- Blood
- Publisher
- American Society of Hematology
- Published
- 2016-08-25
- Volume
- 128
- Issue
- 8
- Pages
- e20-e31
- ISSN
- 0006-4971 (ISSN-L)
- 1528-0020
- PMC
- PMC5305050
- OpenAlex
- W2465917013
- Cited by
- 768
- References
- 55
- Citations by year
- 2026: 46 · 2025: 87 · 2024: 81 · 2023: 89 · 2022: 99 · 2021: 102 · 2020: 104 · 2019: 64 · 2018: 60 · 2017: 31 · 2016: 3
- FWCI
- 27.36
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Blood (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Apollo (University of Cambridge) (acceptedVersion, cc-by)
- Apollo
- Funders
- Wellcome Trust (107630/Z/15/Z, 097922/Z/11/Z)
- Cancer Research UK (12765)
- National Institute for Health and Care Research
- Directorate for Biological Sciences
- Medical Research Council (MR/M008975/1, MC_PC_12009)
- Biotechnology and Biological Sciences Research Council (BB/I00050X/1, 1800757)
- Cambridge Institute for Medical Research, University of Cambridge
- NIHR Cambridge Biomedical Research Centre
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Hematology › Hematopoietic Stem Cell Transplantation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- hematopoietic stem and progenitor cells, single-cell transcriptomics, differentiation trajectories, lymphoid differentiation, erythroid differentiation, cell cycle genes, oxidative phosphorylation, stem cell maintenance, mice
- MeSH terms
- Animals, Cell Cycle, Cell Differentiation, Female, Gene Expression Regulation, Hematopoietic Stem Cells, Mice, Inbred C57BL, Phenotype, RNA, Messenger, Transcription, Genetic, Biomarkers, Gene Expression Profiling, Single-Cell Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review