Single-cell analysis tools for drug discovery and development
Open accessAbstract
The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed.
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
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?
Single-cell RNA sequencing technology has enabled analysis of intercellular heterogeneity at fine resolution and breakthroughs in understanding disease mechanisms.
“Recent significant advances in single-cell technologies, especially the single-cell RNA sequencing (scRNA-seq) technology, have enabled the analysis of intercellular heterogeneity at a very fine resolution8,9 and helped us to have many breakthroughs in understanding disease mechanisms10, such as breast cancer11, liver cancer12 and COVID-1913.”
From ASGARD is a single-cell guided pipeline to aid repurposing of drugs (2023) · cites this paper as [8]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Hallmarks of Cancer: The Next Generation
Hanahan, D., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.02.013 · Cited by 66,590 · see citing works
Towbin, H., Staehelin, T., & Gordon, J. (1979) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.76.9.4350 · Cited by 51,421 · see citing works
Raza, H., John, A., & Nemmar, A. (2013) · Cellular Physiology and Biochemistry · doi:10.1159/000350087 · Cited by 47,311 · see citing works
Microenvironmental regulation of tumor progression and metastasis
Quail, D. F., & Joyce, J. A. (2013) · Nature Medicine · doi:10.1038/nm.3394 · Cited by 7,994 · see citing works
Comprehensive genomic characterization defines human glioblastoma genes and core pathways
The Cancer Genome Atlas Research Network (2008) · Nature · doi:10.1038/nature07385 · Cited by 7,735 · see citing works
Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.
Macosko, E. Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A. R., Kamitaki, N., Martersteck, E. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.002 · Cited by 7,110 · see citing works
Nowell, P. C. (1976) · Science · doi:10.1126/science.959840 · Cited by 6,471 · see citing works
Stochastic Gene Expression in a Single Cell
Elowitz, M. B., Levine, A. J., Siggia, E. D., & Swain, P. S. (2002) · Science · doi:10.1126/science.1070919 · Cited by 5,441 · see citing works
Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma
Patel, A. P., Tirosh, I., Trombetta, J. J., Shalek, A. K., Gillespie, S. M., Wakimoto, H., Cahill, D. P., Nahed, B. V., Curry, W. T., Martuza, R. L., et al. (2014) · Science · doi:10.1126/science.1254257 · Cited by 5,063 · see citing works
The Somatic Genomic Landscape of Glioblastoma
Brennan, C. W., Verhaak, R. G. W., McKenna, A., Campos, B., Noushmehr, H., Salama, S. R., Zheng, S., Chakravarty, D., Sanborn, J. Z., Berman, S. H., et al. (2013) · Cell · doi:10.1016/j.cell.2013.09.034 · Cited by 5,016 · see citing works
Neoantigens in cancer immunotherapy
Schumacher, T. N., & Schreiber, R. D. (2015) · Science · doi:10.1126/science.aaa4971 · Cited by 4,783 · see citing works
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 · see citing works
mRNA-Seq whole-transcriptome analysis of a single cell
Tang, F., Barbacioru, C., Wang, Y., Nordman, E., Lee, C., Xu, N., Wang, X., Bodeau, J., Tuch, B. B., Siddiqui, A., et al. (2009) · Nature Methods · doi:10.1038/nmeth.1315 · Cited by 3,969 · see citing works
Enhancement of Antitumor Immunity by CTLA-4 Blockade
Leach, D. R., Krummel, M. F., & Allison, J. P. (1996) · Science · doi:10.1126/science.271.5256.1734 · Cited by 3,955 · see citing works
Phenotypic Analysis of Antigen-Specific T Lymphocytes
Altman, J. D., Moss, P. A. H., Goulder, P. J. R., Barouch, D. H., McHeyzer-Williams, M. G., Bell, J. I., McMichael, A. J., & Davis, M. M. (1996) · Science · doi:10.1126/science.274.5284.94 · Cited by 3,544 · cited 2× · see citing works
“To understand immune responses to cancer, it is of significant interest to develop approaches that can match the TCR genes with their specific (or cognate) antigen, which usually result from nonsynonymous somatic mutations specific for each cancer 105,133,135–138, 140, 141 .”
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 · see citing works
Iwai, Y., Ishida, M., Tanaka, Y., Okazaki, T., Honjo, T., & Minato, N. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.192461099 · Cited by 3,204 · see citing works
Discovery and saturation analysis of cancer genes across 21 tumour types
Lawrence, M. S., Stojanov, P., Mermel, C. H., Robinson, J. T., Garraway, L. A., Golub, T. R., Meyerson, M., Gabriel, S. B., Lander, E. S., & Getz, G. (2014) · Nature · doi:10.1038/nature12912 · Cited by 3,096 · see citing works
Spatially resolved, highly multiplexed RNA profiling in single cells
Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S., & Zhuang, X. (2015) · Science · doi:10.1126/science.aaa6090 · Cited by 2,969 · see citing works
Bacterial Persistence as a Phenotypic Switch
Balaban, N. Q., Merrin, J., Chait, R., Kowalik, L., & Leibler, S. (2004) · Science · doi:10.1126/science.1099390 · Cited by 2,952 · see citing works
Influence of tumour micro-environment heterogeneity on therapeutic response
Junttila, M. R., & de Sauvage, F. J. (2013) · Nature · doi:10.1038/nature12626 · Cited by 2,694 · see citing works
Tumour evolution inferred by single-cell sequencing
Navin, N., Kendall, J., Troge, J., Andrews, P., Rodgers, L., McIndoo, J., Cook, K., Stepansky, A., Levy, D., Esposito, D., et al. (2011) · Nature · doi:10.1038/nature09807 · Cited by 2,598 · see citing works
Adoptive cell transfer as personalized immunotherapy for human cancer
Rosenberg, S. A., & Restifo, N. P. (2015) · Science · doi:10.1126/science.aaa4967 · Cited by 2,492 · see citing works
Tumour heterogeneity and cancer cell plasticity
Meacham, C., & Morrison, S. (2013) · Nature · doi:10.1038/nature12624 · Cited by 2,350 · see citing works
Bendall, S. C., Simonds, E. F., Qiu, P., Amir, E.-A. D., Krutzik, P. O., Finck, R., Bruggner, R. V., Melamed, R., Trejo, A., Ornatsky, O. I., et al. (2011) · Science · doi:10.1126/science.1198704 · Cited by 2,279 · see citing works
Stochasticity in gene expression: from theories to phenotypes
Kærn, M., Elston, T. C., Blake, W. J., & Collins, J. J. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1615 · Cited by 2,270 · see citing works
Reducing the Effects of PCR Amplification and Sequencing Artifacts on 16S rRNA-Based Studies
Schloss, P. D., Gevers, D., & Westcott, S. L. (2011) · PLoS ONE · doi:10.1371/journal.pone.0027310 · Cited by 2,112 · see citing works
Cancer immunotherapy via dendritic cells
Palucka, K., & Banchereau, J. (2012) · Nature reviews. Cancer · doi:10.1038/nrc3258 · Cited by 2,060 · see citing works
Couzin-Frankel, J. (2013) · Science · doi:10.1126/science.342.6165.1432 · Cited by 2,051 · see citing works
Targeted capture and massively parallel sequencing of 12 human exomes
Ng, S. B., Turner, E. H., Robertson, P. D., Flygare, S. D., Bigham, A. W., Lee, C., Shaffer, T., Wong, M., Bhattacharjee, A., Eichler, E. E., et al. (2009) · Nature · doi:10.1038/nature08250 · Cited by 2,030 · see citing works
Bias caused by template annealing in the amplification of mixtures of 16S rRNA genes by PCR
Suzuki, M. T., & Giovannoni, S. (1996) · Applied and Environmental Microbiology · doi:10.1128/aem.62.2.625-630.1996 · Cited by 2,021 · see citing works
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 · see citing works
Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics
Sottoriva, A., Spiteri, I., Piccirillo, S. G. M., Touloumis, A., Collins, V. P., Marioni, J. C., Curtis, C., Watts, C., & Tavaré, S. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1219747110 · Cited by 1,737 · see citing works
Models, mechanisms and clinical evidence for cancer dormancy
Aguirre‐Ghiso, J. A. (2007) · Nature reviews. Cancer · doi:10.1038/nrc2256 · Cited by 1,673 · see citing works
Adoptive cell transfer: a clinical path to effective cancer immunotherapy
Rosenberg, S. A., Restifo, N. P., Yang, J. C.-H., Morgan, R. A., & Dudley, M. E. (2008) · Nature reviews. Cancer · doi:10.1038/nrc2355 · Cited by 1,654 · see citing works
Stability and Diversity of Ecosystems
Ives, A. R., & Carpenter, S. R. (2007) · Science · doi:10.1126/science.1133258 · Cited by 1,591 · see citing works
Amir, E.-A. D., Davis, K. L., Tadmor, M. D., Simonds, E. F., Levine, J. H., Bendall, S. C., Shenfeld, D. K., Krishnaswamy, S., Nolan, G. P., & Pe'er, D. (2013) · Nature Biotechnology · doi:10.1038/nbt.2594 · Cited by 1,550 · see citing works
Bias in template-to-product ratios in multitemplate PCR
Polz, M. F., & Cavanaugh, C. M. (1998) · Applied and Environmental Microbiology · doi:10.1128/aem.64.10.3724-3730.1998 · Cited by 1,484 · see citing works
Stochastic State Transitions Give Rise to Phenotypic Equilibrium in Populations of Cancer Cells
Gupta, P. B., Fillmore, C. M., Jiang, G., Shapira, S. D., Tao, K., Kuperwasser, C., & Lander, E. S. (2011) · Cell · doi:10.1016/j.cell.2011.07.026 · Cited by 1,475 · see citing works
Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq
Treutlein, B., Brownfield, D. G., Wu, A. R., Neff, N. F., Mantalas, G. L., Espinoza, F. H., Desai, T. J., Krasnow, M. A., & Quake, S. R. (2014) · Nature · doi:10.1038/nature13173 · Cited by 1,342 · see citing works
Selected reaction monitoring–based proteomics: workflows, potential, pitfalls and future directions
Picotti, P., & Aebersold, R. (2012) · Nature Methods · doi:10.1038/nmeth.2015 · Cited by 1,302 · see citing works
Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting
Matsushita, H., Vesely, M. D., Koboldt, D. C., Rickert, C. G., Uppaluri, R., Magrini, V. J., Arthur, C. D., White, J. M., Chen, Y.-S., Shea, L. K., et al. (2012) · Nature · doi:10.1038/nature10755 · Cited by 1,285 · see citing works
Single-cell analysis and sorting using droplet-based microfluidics
Mazutis, L., Gilbert, J., Ung, W. L., Weitz, D., Griffiths, A., & Heyman, J. A. (2013) · Nature Protocols · doi:10.1038/nprot.2013.046 · Cited by 1,267 · see citing works
Target-enrichment strategies for next-generation sequencing
Mamanova, L., Coffey, A. J., Scott, C. E., Kozarewa, I., Turner, E. H., Kumar, A., Howard, E. K., Shendure, J., & Turner, D. (2010) · Nature Methods · doi:10.1038/nmeth.1419 · Cited by 1,221 · see citing works
Tumour heterogeneity in the clinic
Bedard, P. L., Hansen, A. R., Ratain, M. J., & Siu, L. L. (2013) · Nature · doi:10.1038/nature12627 · Cited by 1,214 · see citing works
Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells
Shalek, A. K., Satija, R., Adiconis, X., Gertner, R. S., Gaublomme, J. T., Raychowdhury, R., Schwartz, S., Yosef, N., Malboeuf, C., Lu, D., et al. (2013) · Nature · doi:10.1038/nature12172 · Cited by 1,190 · see citing works
Quantitative single-cell RNA-seq with unique molecular identifiers
Islam, S., Zeisel, A., Joost, S., La Manno, G., Zajac, P., Kasper, M., Lönnerberg, P., & Linnarsson, S. (2014) · Nature Methods · doi:10.1038/nmeth.2772 · Cited by 1,183 · see citing works
Single-cell sequencing-based technologies will revolutionize whole-organism science
Shapiro, E., Biezuner, T., & Linnarsson, S. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3542 · Cited by 1,177 · see citing works
Genome-Wide Detection of Single-Nucleotide and Copy-Number Variations of a Single Human Cell
Zong, C., Lu, S., Chapman, A. R., & Xie, X. S. (2012) · Science · doi:10.1126/science.1229164 · Cited by 1,154 · see citing works
Tumour antigens recognized by T lymphocytes: at the core of cancer immunotherapy
Coulie, P. G., den Eynde, B. J. V., van der Bruggen, P., & Boon, T. (2014) · Nature reviews. Cancer · doi:10.1038/nrc3670 · Cited by 1,142 · see citing works
Characterization of circulating T cells specific for tumor-associated antigens in melanoma patients
Lee, P. P., Yee, C., Savage, P. A., Fong, L. H., Brockstedt, D. G., Weber, J. S., Johnson, D. L., Swetter, S. M., Thompson, J. A., Greenberg, P. D., et al. (1999) · Nature Medicine · doi:10.1038/9525 · Cited by 1,117 · see citing works
Multiplexed ion beam imaging of human breast tumors
Angelo, M., Bendall, S. C., Finck, R., Hale, M. B., Hitzman, C., Borowsky, A. D., Levenson, R. M., Lowe, J. B., Liu, S. D., Zhao, S., et al. (2014) · Nature Medicine · doi:10.1038/nm.3488 · Cited by 1,108 · see citing works
Proteomics by Mass Spectrometry: Approaches, Advances, and Applications
Yates, J. R., Ruse, C. I., & Nakorchevsky, A. (2009) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-061008-124934 · Cited by 1,078 · see citing works
Robbins, P. F., Lu, Y., El‐Gamil, M., Li, Y. F., Gross, C. A., Gartner, J. J., Lin, J., Teer, J. K., Cliften, P. F., Tycksen, E., et al. (2013) · Nature Medicine · doi:10.1038/nm.3161 · Cited by 1,074 · see citing works
Dean, F. B., Nelson, J. R., Giesler, T. L., & Lasken, R. S. (2001) · Genome Research · doi:10.1101/gr.180501 · Cited by 1,070 · see citing works
Droplet microfluidic technology for single-cell high-throughput screening
Brouzes, E., Medkova, M., Savenelli, N., Marran, D., Twardowski, M., Hutchison, J. B., Rothberg, J., Link, D., Perrimon, N., & Samuels, M. (2009) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.0903542106 · Cited by 1,064 · see citing works
Czerkinsky, C. C., Nilsson, L., Nygren, H., Ouchterlony, Ö., & Tarkowski, A. (1983) · Journal of Immunological Methods · doi:10.1016/0022-1759(83)90308-3 · Cited by 1,056 · see citing works
Droplet microfluidics for high-throughput biological assays
Guo, M., Rotem, A., Heyman, J. A., & Weitz, D. A. (2012) · Lab on a Chip · doi:10.1039/c2lc21147e · Cited by 1,044 · see citing works
Seventeen-colour flow cytometry: unravelling the immune system
Perfetto, S. P., Chattopadhyay, P. K., & Roederer, M. (2004) · Nature Reviews Immunology · doi:10.1038/nri1416 · Cited by 1,019 · see citing works
Counting absolute numbers of molecules using unique molecular identifiers
Kivioja, T., Vähärautio, A., Karlsson, K., Bonke, M., Enge, M., Linnarsson, S., & Taipale, J. (2012) · Nature Methods · doi:10.1038/nmeth.1778 · Cited by 1,010 · see citing works
Single-cell in situ RNA profiling by sequential hybridization
Lubeck, E., Coskun, A. F., Zhiyentayev, T., Ahmad, M., & Cai, L. (2014) · Nature Methods · doi:10.1038/nmeth.2892 · Cited by 985 · see citing works
Accounting for technical noise in single-cell RNA-seq experiments
Brennecke, P., Anders, S., Kim, J. K., Kołodziejczyk, A. A., Zhang, X., Proserpio, V., Baying, B., Benes, V., Teichmann, S. A., Marioni, J. C., et al. (2013) · Nature Methods · doi:10.1038/nmeth.2645 · Cited by 979 · see citing works
Analysis of gene expression in single live neurons.
Eberwine, J. H., Yeh, H., Miyashiro, K., Cao, Y., Nair, S., Finnell, R. H., Zettel, M. F., & Coleman, P. D. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.7.3010 · Cited by 953 · see citing works
Single-Cell Phenotyping within Transparent Intact Tissue through Whole-Body Clearing
Yang, B., Treweek, J. B., Kulkarni, R. P., Deverman, B. E., Chen, C., Lubeck, E., Shah, S., Cai, L., & Gradinaru, V. (2014) · Cell · doi:10.1016/j.cell.2014.07.017 · Cited by 933 · see citing works
Pollen, A. A., Nowakowski, T. J., Shuga, J., Wang, X., Leyrat, A. A., Lui, J. H., Li, N., Szpankowski, L., Fowler, B., Chen, P., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.2967 · Cited by 920 · see citing works
Whole genome amplification from a single cell: implications for genetic analysis.
Zhang, L., Cui, X., Schmitt, K., Hubert, R., Navidi, W. C., & Arnheim, N. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.13.5847 · Cited by 897 · see citing works
The single cell gel electrophoresis assay (comet assay): A European review
McKelvey‐Martin, V. J., Green, M. H. L., Schmezer, P., Pool-Zobel, B. L., Méo, M. D., & Collins, A. R. (1993) · Mutation research. Fundamental and molecular mechanisms of mutagenesis · doi:10.1016/0027-5107(93)90207-v · Cited by 893 · see citing works
Quiescent haematopoietic stem cells are activated by IFN-γ in response to chronic infection
Baldridge, M. T., King, K. Y., Boles, N. C., Weksberg, D. C., & Goodell, M. A. (2010) · Nature · doi:10.1038/nature09135 · Cited by 877 · see citing works
Toll-like Receptors on Hematopoietic Progenitor Cells Stimulate Innate Immune System Replenishment
Nagai, Y., Garrett, K. P., Ohta, S., Bahrun, U., Kouro, T., Akira, S., Takatsu, K., & Kincade, P. W. (2006) · Immunity · doi:10.1016/j.immuni.2006.04.008 · Cited by 834 · see citing works
Immunological method for mapping genes on Drosophila polytene chromosomes.
Langer-Safer, P. R., Levine, M., & Ward, D. C. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.14.4381 · Cited by 801 · see citing works
van Rooij, N., van Buuren, M. M., Philips, D., Velds, A., Toebes, M., Heemskerk, B., van Dijk, L. J. A., Behjati, S., Hilkmann, H., el Atmioui, D., et al. (2013) · Journal of Clinical Oncology · doi:10.1200/jco.2012.47.7521 · Cited by 798 · see citing works
Single-cell NF-κB dynamics reveal digital activation and analogue information processing
Tay, S., Hughey, J., Lee, T. K., Lipniacki, T., Quake, S. R., & Covert, M. W. (2010) · Nature · doi:10.1038/nature09145 · Cited by 790 · see citing works
Amann, R., & Fuchs, B. M. (2008) · Nature Reviews Microbiology · doi:10.1038/nrmicro1888 · Cited by 770 · see citing works
Patch Clamp Techniques for Studying Ionic Channels in Excitable Membranes
Sakmann, B. J., & Neher, E. (1984) · Annual Review of Physiology · doi:10.1146/annurev.ph.46.030184.002323 · Cited by 761 · see citing works
Validation of noise models for single-cell transcriptomics
Grün, D., Kester, L., & van Oudenaarden, A. (2014) · Nature Methods · doi:10.1038/nmeth.2930 · Cited by 721 · see citing works
Targeted Therapy Resistance Mediated by Dynamic Regulation of Extrachromosomal Mutant EGFR DNA
Nathanson, D. A., Gini, B., Mottahedeh, J., Visnyei, K., Koga, T., Gomez, G. G., Eskin, A., Hwang, K., Wang, J., Masui, K., et al. (2013) · Science · doi:10.1126/science.1241328 · Cited by 699 · see citing works
Self-citationQuantitative assessment of single-cell RNA-sequencing methods
Wu, A. R., Neff, N. F., Kalisky, T., Dalerba, P., Treutlein, B., Rothenberg, M. E., Mburu, F. M., Mantalas, G. L., Sim, S., Clarke, M. F., et al. (2014) · Nature Methods · doi:10.1038/nmeth.2694 · Cited by 696 · see citing works
Single-cell dissection of transcriptional heterogeneity in human colon tumors
Dalerba, P. D., Tomer Kalisky, C., Sahoo, D., Rajendran, P. S., Rothenberg, M. E., Leyrat, A. A., Sim, S., Okamoto, J., Johnston, D. M., Qian, D., et al. (2011) · Nature Biotechnology · doi:10.1038/nbt.2038 · Cited by 693 · see citing works
Single Cell Profiling of Potentiated Phospho-Protein Networks in Cancer Cells
Irish, J. M., Hovland, R., Krutzik, P. O., Perez, O. D., Bruserud, Ø., Gjertsen, B. T., & Nolan, G. P. (2004) · Cell · doi:10.1016/j.cell.2004.06.028 · Cited by 684 · see citing works
Genome-wide in situ exon capture for selective resequencing
Hodges, E. C., Xuan, Z., Balija, V. S., Kramer, M., Molla, M. N., Smith, S. W., Middle, C. M., Rodesch, M. J., Albert, T. J., Hannon, G. J., et al. (2007) · Nature Genetics · doi:10.1038/ng.2007.42 · Cited by 677 · see citing works
Single-Cell Exome Sequencing Reveals Single-Nucleotide Mutation Characteristics of a Kidney Tumor
Xu, X., Hou, Y., Yin, X., Bao, L., Tang, A., Song, L., Li, F., Tsang, S., Wu, K., Wu, H., et al. (2012) · Cell · doi:10.1016/j.cell.2012.02.025 · Cited by 667 · see citing works
Epidermal growth factor receptor and Ink4a/Arf
Bachoo, R. M., Maher, E. A., Ligon, K. L., Sharpless, N. E., Chan, S., You, M. J., Tang, Y., DeFrances, J., Stover, E. H., Weissleder, R., et al. (2002) · Cancer Cell · doi:10.1016/s1535-6108(02)00046-6 · Cited by 650 · see citing works
Losick, R. M., & Desplan, C. (2008) · Science · doi:10.1126/science.1147888 · Cited by 627 · see citing works
Acinas, S. G., Sarma-Rupavtarm, R., Klepac-Ceraj, V., & Polz, M. F. (2005) · Applied and Environmental Microbiology · doi:10.1128/aem.71.12.8966-8969.2005 · Cited by 625 · see citing works
Herzenberg, L. A., Parks, D. R., Sahaf, B., Perez, O. D., Roederer, M., & Herzenberg, L. A. (2002) · Clinical Chemistry · doi:10.1093/clinchem/48.10.1819 · Cited by 603 · see citing works
Paths to stemness: building the ultimate antitumour T cell
Gattinoni, L., Klebanoff, C. A., & Restifo, N. P. (2012) · Nature reviews. Cancer · doi:10.1038/nrc3322 · Cited by 599 · see citing works
Phenotypic analysis of antigen-specific T lymphocytes. Science. 1996. 274: 94-96.
Altman, J. D., Moss, P. A. H., Goulder, P., Barouch, D. H., McHeyzer‐Williams, M. G., Bell, J. I., McMichael, A. J., & Davis, M. M. (2011) · PubMed · Cited by 572 · see citing works
Inflammatory modulation of HSCs: viewing the HSC as a foundation for the immune response
King, K. Y., & Goodell, M. A. (2011) · Nature reviews. Immunology · doi:10.1038/nri3062 · Cited by 565 · see citing works
Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators
Bodenmiller, B., Zunder, E. R., Finck, R., Chen, T. J., Savig, E. S., Bruggner, R. V., Simonds, E. F., Bendall, S. C., Sachs, K., Krutzik, P. O., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2317 · Cited by 546 · see citing works
Inda, M.-D.-M., Bonavia, R., Mukasa, A., Narita, Y., Sah, D. W. Y., VandenBerg, S. R., Brennan, C. W., Johns, T. G., Bachoo, R. M., Hadwiger, P., et al. (2010) · Genes & Development · doi:10.1101/gad.1890510 · Cited by 543 · see citing works
Single-Cell Exome Sequencing and Monoclonal Evolution of a JAK2-Negative Myeloproliferative Neoplasm
Hou, Y., Song, L., Zhu, P., Zhang, B., Tao, Y., Xu, X., Li, F., Wu, K., Liang, J., Shao, D., et al. (2012) · Cell · doi:10.1016/j.cell.2012.02.028 · Cited by 541 · see citing works
Linking T-cell receptor sequence to functional phenotype at the single-cell level
Han, A. S., Glanville, J., Hansmann, L., & Davis, M. M. (2014) · Nature Biotechnology · doi:10.1038/nbt.2938 · Cited by 534 · see citing works
Whole-exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer
Lohr, J. G., Adalsteinsson, V. A., Cibulskis, K., Choudhury, A. D., Rosenberg, M. W., Cruz‐Gordillo, P., Francis, J. M., Zhang, C.-Z., Shalek, A. K., Satija, R., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.2892 · Cited by 534 · see citing works
Powell, A. A., Talasaz, A. H., Zhang, H., Coram, M., Reddy, A., Deng, G. Y., Telli, M. L., Advani, R. H., Carlson, R. W., Mollick, J. A., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0033788 · Cited by 531 · see citing works
Expression of tumour-specific antigens underlies cancer immunoediting
DuPage, M. J. P., Mazumdar, C., Schmidt, L., Cheung, A. F., & Jacks, T. (2012) · Nature · doi:10.1038/nature10803 · Cited by 529 · see citing works
Ting, D. T., Wittner, B. S., Ligorio, M., Jordan, N. V., Shah, A. M., Miyamoto, D. T., Aceto, N., Bersani, F., Brannigan, B. W., Xega, K., et al. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.08.029 · Cited by 521 · see citing works
Genome-wide Single-Cell Analysis of Recombination Activity and De Novo Mutation Rates in Human Sperm
Wang, J., Fan, H. C., Behr, B. R., & Quake, S. R. (2012) · Cell · doi:10.1016/j.cell.2012.06.030 · Cited by 511 · see citing works
Cellular Heterogeneity and Molecular Evolution in Cancer
Almendro, V., Marusyk, A., & Polyák, K. (2012) · Annual Review of Pathology Mechanisms of Disease · doi:10.1146/annurev-pathol-020712-163923 · Cited by 491 · see citing works
Automated identification of stratifying signatures in cellular subpopulations
Bruggner, R. V., Bodenmiller, B., Dill, D. L., Tibshirani, R. J., & Nolan, G. P. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1408792111 · Cited by 457 · see citing works
Rosa, S. C. D., Herzenberg, L. A., Herzenberg, L. A., & Roederer, M. (2001) · Nature Medicine · doi:10.1038/84701 · Cited by 455 · see citing works
Combinatorial labeling of single cells for gene expression cytometry
Fan, H. C., Fu, G. K., & Fodor, S. P. A. (2015) · Science · doi:10.1126/science.1258367 · Cited by 455 · see citing works
Ni, X., Zhuo, M., Su, Z., Duan, J., Gao, Y., Wang, Z., Zong, C., Bai, H., Chapman, A. R., Zhao, J., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1320659110 · Cited by 454 · see citing works
A microengraving method for rapid selection of single cells producing antigen-specific antibodies
Love, J. C., Ronan, J. L., Grotenbreg, G. M., van der Veen, A. G., & Ploegh, H. L. (2006) · Nature Biotechnology · doi:10.1038/nbt1210 · Cited by 453 · see citing works
Ma, C., Fan, R., Ahmad, H., Shi, Q., Comin-Anduix, B., Chodon, T., Koya, R. C., Liu, C.-C., Kwong, G. A., Radu, C. G., et al. (2011) · Nature Medicine · doi:10.1038/nm.2375 · Cited by 441 · see citing works
Self-citationEpitope Landscape in Breast and Colorectal Cancer
Segal, N. H., Parsons, D. W., Peggs, K. S., Velculescu, V., Kinzler, K. W., Vogelstein, B., & Allison, J. P. (2008) · Cancer Research · doi:10.1158/0008-5472.can-07-3095 · Cited by 416 · see citing works
Hughes, A. J., Spelke, D. P., Xu, Z., Kang, C., Schaffer, D. V., & Herr, A. E. (2014) · Nature Methods · doi:10.1038/nmeth.2992 · Cited by 415 · see citing works
Bengtsson, M., Ståhlberg, A., Rorsman, P., & Kubista, M. (2005) · Genome Research · doi:10.1101/gr.3820805 · Cited by 392 · see citing works
Heterogeneity of epidermal growth factor receptor signalling networks in glioblastoma
Furnari, F. B., Cloughesy, T. F., Cavenee, W. K., & Mischel, P. S. (2015) · Nature reviews. Cancer · doi:10.1038/nrc3918 · Cited by 378 · see citing works
Self-citationHuebner, A., Bratton, D., Whyte, G., Yang, M., deMello, A. J., Abell, C., & Hollfelder, F. (2008) · Lab on a Chip · doi:10.1039/b813709a · Cited by 347 · see citing works
Inflammatory signals regulate hematopoietic stem cells
Baldridge, M. T., King, K., & Goodell, M. (2011) · Trends in immunology · doi:10.1016/j.it.2010.12.003 · Cited by 337 · see citing works
Zhao, J. L., Ma, C., O’Connell, R. M., Mehta, A., DiLoreto, R., Heath, J. R., & Baltimore, D. (2014) · Cell stem cell · doi:10.1016/j.stem.2014.01.007 · Cited by 333 · see citing works
Self-citationPolyfunctional responses by human T cells result from sequential release of cytokines
Han, Q., Bagheri, N., Bradshaw, E. M., Hafler, D. A., Lauffenburger, D. A., & Love, J. C. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1117194109 · Cited by 329 · see citing works
Generation of peptide–MHC class I complexes through UV-mediated ligand exchange
Rodenko, B., Toebes, M., Hadrup, S. R., van Esch, W. J. E., Molenaar, A. M., Schumacher, T. N., & Ovaa, H. (2006) · Nature Protocols · doi:10.1038/nprot.2006.121 · Cited by 320 · see citing works
Single-cell proteomic chip for profiling intracellular signaling pathways in single tumor cells
Shi, Q., Qin, L., Wei, W., Geng, F., Fan, R., Shin, Y. S., Guo, D., Hood, L., Mischel, P. S., & Heath, J. R. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1110865109 · Cited by 318 · see citing works
Self-citationA Quantitative Comparison of Single-Cell Whole Genome Amplification Methods
de Bourcy, C. F. A., Vlaminck, I. D., Kanbar, J. N., Wang, J., Gawad, C., & Quake, S. R. (2014) · PLoS ONE · doi:10.1371/journal.pone.0105585 · Cited by 305 · see citing works
Gill, B. J. A., Pisapia, D. J., Malone, H. R., Goldstein, H. E., Lei, L., Sonabend, A. M., Yun, J. J., Samanamud, J. L., Sims, J. S., Banu, M. A., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1405839111 · Cited by 299 · see citing works
<i>EGFR</i> Variant Heterogeneity in Glioblastoma Resolved through Single-Nucleus Sequencing
Francis, J. M., Zhang, C.-Z., Maire, C. L., Jung, J., Manzo, V. E., Adalsteinsson, V. A., Homer, H., Haidar, S., Blumenstiel, B., Pedamallu, C. S., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0879 · Cited by 287 · see citing works
Single-Cell Transcriptome Analyses Reveal Signals to Activate Dormant Neural Stem Cells
Luo, Y., Coskun, V., Liang, A., Yu, J., Cheng, L., Ge, W., Shi, Z., Zhang, K., Li, C., Cui, Y., et al. (2015) · Cell · doi:10.1016/j.cell.2015.04.001 · Cited by 263 · see citing works
Lu, Y., Xue, Q., Eisele, M. R., Sulistijo, E., Brower, K., Han, L., Amir, E., Pe'er, D., Miller-Jensen, K., & Fan, R. (2015) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.1416756112 · Cited by 246 · see citing works
Life history trade-offs in cancer evolution
Aktipis, A., Boddy, A. M., Gatenby, R. A., Brown, J. S., & Maley, C. C. (2013) · Nature reviews. Cancer · doi:10.1038/nrc3606 · Cited by 236 · see citing works
Julius, M. H., Masuda, T., & Herzenberg, L. A. (1972) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.69.7.1934 · Cited by 232 · see citing works
Lineage relationship of effector and memory T cells
Restifo, N. P., & Gattinoni, L. (2013) · Current Opinion in Immunology · doi:10.1016/j.coi.2013.09.003 · Cited by 230 · see citing works
NanoFlares for the detection, isolation, and culture of live tumor cells from human blood
Halo, T. L., McMahon, K. M., Angeloni, N. L., Xu, Y., Wang, W., Chinen, A. B., Malin, D., Strekalova, E., Cryns, V. L., Cheng, C., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1418637111 · Cited by 222 · see citing works
Noise Facilitates Transcriptional Control under Dynamic Inputs
Kellogg, R., & Tay, S. (2015) · Cell · doi:10.1016/j.cell.2015.01.013 · Cited by 213 · see citing works
Semenza, G. L. (2012) · Oncogene · doi:10.1038/onc.2012.578 · Cited by 201 · see citing works
Paired analysis of TCRα and TCRβ chains at the single-cell level in mice
Dash, P., McClaren, J. L., Oguin, T. H., Rothwell, W. T., Todd, B., Morris, M. Y., Becksfort, J. B., Reynolds, C., Brown, S. A., Doherty, P. C., et al. (2010) · Journal of Clinical Investigation · doi:10.1172/jci44752 · Cited by 199 · see citing works
High-Throughput Secretomic Analysis of Single Cells to Assess Functional Cellular Heterogeneity
Lu, Y., Chen, J. J. F., Mu, L., Xue, Q., Wu, Y., Wu, P.-H., Li, J., Vortmeyer, A. O., Miller‐Jensen, K., Wirtz, D., et al. (2013) · Analytical Chemistry · doi:10.1021/ac400082e · Cited by 173 · see citing works
Computational Approaches for Analyzing Information Flow in Biological Networks
Kholodenko, B. Ν., Yaffe, M. B., & Kölch, W. (2012) · Science Signaling · doi:10.1126/scisignal.2002961 · Cited by 170 · see citing works
Microfluidic droplets: new integrated workflows for biological experiments
Kintses, B., van Vliet, L., Devenish, S. R. A., & Hollfelder, F. (2010) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2010.08.013 · Cited by 168 · see citing works
Bakker, A., Hoppes, R., Linnemann, C., Toebes, M., Rodenko, B., Berkers, C. R., Hadrup, S. R., van Esch, W. J. E., Heemskerk, M. H. M., Ovaa, H., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0709717105 · Cited by 151 · see citing works
Porichis, F., Hart, M. G., Griesbeck, M., Everett, H. L., Hassan, M., Baxter, A. E., Lindqvist, M., Miller, S. M., Soghoian, D. Z., Kavanagh, D. G., et al. (2014) · Nature Communications · doi:10.1038/ncomms6641 · Cited by 150 · see citing works
Dago, A. E., Stepansky, A., Carlsson, A., Luttgen, M. S., Kendall, J., Baslan, T., Kolatkar, A. R., Wigler, M. H., Bethel, K. J., Gross, M. E., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0101777 · Cited by 148 · see citing works
Ma, C., Cheung, A. F., Chodon, T., Koya, R. C., Wu, Z., Ng, C., Avramis, E. V., Cochran, A. J., Witte, O. N., Baltimore, D., et al. (2013) · Cancer Discovery · doi:10.1158/2159-8290.cd-12-0383 · Cited by 144 · see citing works
Self-citationNonequilibrium Statistical Physics of Small Systems
(2013) · Wiley eBooks · doi:10.1002/9783527658701 · Cited by 141 · see citing works
Marcon, E., Jain, H., Bhattacharya, A., Guo, H., Phanse, S., Pu, S., Byram, G., Collins, B. C., Dowdell, E., Fenner, M., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3472 · Cited by 127 · see citing works
Uncoupling T‐cell expansion from effector differentiation in cell‐based immunotherapy
Crompton, J. G., Sukumar, M., & Restifo, N. P. (2013) · Immunological Reviews · doi:10.1111/imr.12135 · Cited by 120 · see citing works
High-throughput microfluidic single-cell analysis pipeline for studies of signaling dynamics
Kellogg, R., Gómez-Sjöberg, R., Leyrat, A. A., & Tay, S. (2014) · Nature Protocols · doi:10.1038/nprot.2014.120 · Cited by 117 · see citing works
Analysis of the Paired TCR α- and β-chains of Single Human T Cells
Kim, S.-M., Bhonsle, L., Besgen, P., Nickel, J., Backes, A., Held, K., Vollmer, S., Dornmair, K., & Prinz, J. C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037338 · Cited by 107 · see citing works
Fu, G. K., Xu, W., Wilhelmy, J., Mindrinos, M. N., Davis, R. W., Xiao, W., & Fodor, S. P. A. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1323732111 · Cited by 106 · see citing works
Dissecting genomic diversity, one cell at a time
Blainey, P. C., & Quake, S. R. (2013) · Nature Methods · doi:10.1038/nmeth.2783 · Cited by 102 · see citing works
Yamanaka, Y. J., Berger, C. T., Sips, M., Cheney, P. C., Alter, G., & Love, J. C. (2012) · Integrative Biology · doi:10.1039/c2ib20167d · Cited by 102 · see citing works
Liadi, I., Singh, H., Romain, G., Rey-Villamizar, N., Merouane, A., Adolacion, J. R. T., Kebriaei, P., Huls, H. M., Qiu, P., Roysam, B., et al. (2015) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-14-0195 · Cited by 100 · see citing works
Romain, G., Senyukov, V., Rey-Villamizar, N., Merouane, A., Kelton, W., Liadi, I., Mahendra, A., Charab, W., Georgiou, G., Roysam, B., et al. (2014) · Blood · doi:10.1182/blood-2014-04-569061 · Cited by 98 · see citing works
High sensitivity of cancer exome-based CD8 T cell neo-antigen identification
van Buuren, M. M., Calis, J. J. A., & Schumacher, T. N. (2014) · OncoImmunology · doi:10.4161/onci.28836 · Cited by 93 · see citing works
Chemical Methods for the Simultaneous Quantitation of Metabolites and Proteins from Single Cells
Xue, M., Wei, W., Su, Y., Kim, J.-W., Shin, Y. S., Mai, W. X., Nathanson, D. A., & Heath, J. R. (2015) · Journal of the American Chemical Society · doi:10.1021/jacs.5b00944 · Cited by 93 · see citing works
Self-citationModular Nucleic Acid Assembled p/MHC Microarrays for Multiplexed Sorting of Antigen-Specific T Cells
Kwong, G. A., Radu, C. G., Hwang, K., Shu, C. J., Ma, C., Koya, R. C., Comin-Anduix, B., Hadrup, S. R., Bailey, R. C., Witte, O. N., et al. (2009) · Journal of the American Chemical Society · doi:10.1021/ja9006707 · Cited by 89 · see citing works
Self-citationThe Future of Cancer Therapy: Selecting Patients Likely to Respond to PD1/L1 Blockade
Ribas, A., & Tumeh, P. C. (2014) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-14-0933 · Cited by 88 · see citing works
Self-citationHan, L., Zi, X., Garmire, L. X., Wu, Y., Weissman, S. M., Pan, X., & Fan, R. (2014) · Scientific Reports · doi:10.1038/srep06485 · Cited by 83 · see citing works
Wang, J., Tham, D., Wei, W., Shin, Y. S., Ma, C., Ahmad, H. M. N., Shi, Q., Yu, J.-K., Levine, R. D., & Heath, J. R. (2012) · Nano Letters · doi:10.1021/nl302748q · Cited by 80 · see citing works
Self-citationQuantitative PCR Analysis of DNA, RNAs, and Proteins in the Same Single Cell
Ståhlberg, A., Thomsen, C., Ruff, D., & Åman, P. (2012) · Clinical Chemistry · doi:10.1373/clinchem.2012.191445 · Cited by 78 · see citing works
Yu, J., Zhou, J., Sutherland, A., Wei, W., Shin, Y. S., Xue, M., & Heath, J. R. (2014) · Annual Review of Analytical Chemistry · doi:10.1146/annurev-anchem-071213-020323 · Cited by 72 · see citing works
Self-citationThe Scientific Drunk and the Lamppost: Massive Sequencing Efforts in Cancer Discovery and Treatment
Yaffe, M. B. (2013) · Science Signaling · doi:10.1126/scisignal.2003684 · Cited by 67 · see citing works
Weingeist, D. M., Ge, J., Wood, D. K., Mutamba, J. T., Huang, Q., Rowland, E. A., Yaffe, M. B., Floyd, S., & Engelward, B. P. (2013) · Cell Cycle · doi:10.4161/cc.23880 · Cited by 64 · see citing works
Tumor Heterogeneity Confounds and Illuminates: A case for Darwinian tumor evolution
Polyák, K. (2014) · Nature Medicine · doi:10.1038/nm.3518 · Cited by 63 · see citing works
Hypoxia induces a phase transition within a kinase signaling network in cancer cells
Wei, W., Shi, Q., Remacle, F., Qin, L., Shackelford, D. B., Shin, Y. S., Mischel, P. S., Levine, R. D., & Heath, J. R. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1303060110 · Cited by 63 · see citing works
Self-citationTorres, A. J., Contento, R. L., Gordo, S., Wucherpfennig, K. W., & Love, J. C. (2012) · Lab on a Chip · doi:10.1039/c2lc40869d · Cited by 60 · see citing works
A microchip platform for interrogating tumor–macrophage paracrine signaling at the single-cell level
Elitaş, M., Brower, K. K., Lu, Y., Chen, J. J. F., & Fan, R. (2014) · Lab on a Chip · doi:10.1039/c4lc00676c · Cited by 57 · see citing works
EGFR and EGFRvIII in Glioblastoma: Partners in Crime
Zadeh, G. M., Bhat, K., & Aldape, K. (2013) · Cancer Cell · doi:10.1016/j.ccr.2013.09.017 · Cited by 56 · see citing works
Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling
Shin, Y. S., Remacle, F., Fan, R., Hwang, K., Wei, W., Ahmad, H. M. N., Levine, R. D., & Heath, J. R. (2011) · Biophysical Journal · doi:10.1016/j.bpj.2011.04.025 · Cited by 56 · see citing works
Self-citationKravchenko‐Balasha, N., Wang, J., Remacle, F., Levine, R. D., & Heath, J. R. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1404462111 · Cited by 54 · see citing works
Self-citationNew directions in cellular therapy of cancer: a summary of the summit on cellular therapy for cancer
Stroncek, D. F., Berger, C., Cheever, M. A., Childs, R. W., Dudley, M. E., Flynn, P., Gattinoni, L., Heath, J. R., Kalos, M. D., Marincola, F. M., et al. (2012) · Journal of Translational Medicine · doi:10.1186/1479-5876-10-48 · Cited by 52 · see citing works
Self-citationShin, Y. S., Ahmad, H. M. N., Shi, Q., Kim, H., Pascal, T. A., Fan, R., Goddard, W. A., & Heath, J. R. (2010) · ChemPhysChem · doi:10.1002/cphc.201000528 · Cited by 52 · see citing works
Self-citationCancer treatment: The killer within
Ledford, H. K. (2014) · Nature · doi:10.1038/508024a · Cited by 48 · see citing works
Real-time tracking, retrieval and gene expression analysis of migrating human T cells
Mehling, M., Frank, T., Albayrak, C., & Tay, S. (2014) · Lab on a Chip · doi:10.1039/c4lc01038h · Cited by 39 · see citing works
UV-Induced Ligand Exchange in MHC Class I Protein Crystals
Celie, P. H. N., Toebes, M., Rodenko, B., Ovaa, H., Anastassis Perrakis, A., & Schumacher, T. N. (2009) · Journal of the American Chemical Society · doi:10.1021/ja9037559 · Cited by 35 · see citing works
Lin, L., Ma, C., Wei, B., Aziz, N., Rajalingam, R., Yusung, S. A., Erlich, H. A., Trachtenberg, E., Targan, S. R., McGovern, D. P. B., et al. (2014) · The Journal of Immunology · doi:10.4049/jimmunol.1400093 · Cited by 33 · see citing works
Self-citationA robust method for production of MHC tetramers with small molecule fluorophores
Ramachandiran, V., Grigoriev, V. G., Lan, L., Ravkov, E. V., Mertens, S. A., & Altman, J. D. (2006) · Journal of Immunological Methods · doi:10.1016/j.jim.2006.08.014 · Cited by 31 · see citing works
Fu, G. K., Wilhelmy, J., Stern, D., Fan, H. C., & Fodor, S. P. A. (2014) · Analytical Chemistry · doi:10.1021/ac500459p · Cited by 29 · see citing works
Bordon, Y. (2014) · Nature reviews. Cancer · doi:10.1038/nrc3880 · Cited by 25 · see citing works
Hematopoietic Stem and Progenitor Cells and the Inflammatory Response
Jaiswal, S., & Weissman, I. L. (2009) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2009.04930.x · Cited by 19 · see citing works
HSPCs Get Their Motors Running for Asymmetric Fate Choice
Zheng, Y., & Geiger, H. (2014) · Cell stem cell · doi:10.1016/j.stem.2013.12.002 · Cited by 18 · see citing works
Detection and isolation of auto-reactive human antibodies from primary B cells
Sendra, V. G., Lie, A., Romain, G., Agarwal, S. K., & Varadarajan, N. (2013) · Methods · doi:10.1016/j.ymeth.2013.06.018 · Cited by 17 · see citing works
Mazumder, A., Tummler, K., Bathe, M., & Samson, L. D. (2012) · Molecular and Cellular Biology · doi:10.1128/mcb.01020-12 · Cited by 14 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Engineering and Design of Chimeric Antigen Receptors
Guedan, S., Calderon, H., Posey, A., & Maus, M. V. (2018) · Molecular Therapy: Methods & Clinical Development · doi:10.1016/j.omtm.2018.12.009 · Cited by 407 · see citing works
DNA methylation: An epigenetic mark of cellular memory
Kim, M., & Costello, J. (2017) · Experimental & Molecular Medicine · doi:10.1038/emm.2017.10 · Cited by 450 · see citing works
Paving the way to single-molecule protein sequencing
Restrepo-Pérez, L., Joo, C., & Dekker, C. (2018) · Nature Nanotechnology · doi:10.1038/s41565-018-0236-6 · Cited by 397 · see citing works
Rubin, A. J., Parker, K. R., Satpathy, A. T., Qi, Y., Wu, B., Ong, A. J., Mumbach, M. R., Ji, A. L., Kim, D. S., Cho, S. W., et al. (2019) · Cell · doi:10.1016/j.cell.2018.11.022 · Cited by 314 · see citing works
Utilizing graph machine learning within drug discovery and development
Gaudelet, T., Day, B., Jamasb, A. R., Soman, J., Regep, C., Liu, G., Hayter, J. B. R., Vickers, R., Roberts, C., Tang, J., et al. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab159 · Cited by 313 · see citing works
Single-cell metabolic profiling of human cytotoxic T cells
Hartmann, F. J., Mrdjen, D., McCaffrey, E., Glass, D. R., Greenwald, N. F., Bharadwaj, A., Khair, Z., Verberk, S. G. S., Baranski, A., Baskar, R., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0651-8 · Cited by 310 · see citing works
The heterogeneity of cellular senescence: insights at the single-cell level
Cohn, R. L., Gasek, N. S., Kuchel, G. A., & Xu, M. (2023) · Trends in Cell Biology · doi:10.1016/j.tcb.2022.04.011 · Cited by 294 · see citing works
Single‐Cell Analysis Using Droplet Microfluidics
Matuła, K., Rivello, F., & Huck, W. T. S. (2019) · Advanced Biosystems · doi:10.1002/adbi.201900188 · Cited by 276 · see citing works
Using single-cell genomics to understand developmental processes and cell fate decisions
Griffiths, J. A., Scialdone, A., & Marioni, J. C. (2018) · Molecular Systems Biology · doi:10.15252/msb.20178046 · Cited by 250 · see citing works
Nanotechnology Strategies To Advance Outcomes in Clinical Cancer Care
Hartshorn, C. M., Bradbury, M. S., Lanza, G. M., Nel, A. E., Rao, J., Wang, A. Z., Wiesner, U. B., Yang, L. P. H., & Grodzinski, P. A. (2017) · ACS Nano · doi:10.1021/acsnano.7b05108 · Cited by 263 · see citing works
Bioinformatics and Drug Discovery
Xia, X. (2017) · Current Topics in Medicinal Chemistry · doi:10.2174/1568026617666161116143440 · Cited by 256 · see citing works
The Human Protein Atlas—Spatial localization of the human proteome in health and disease
Digre, A., & Lindskog, C. (2020) · Protein Science · doi:10.1002/pro.3987 · Cited by 247 · see citing works
Generative artificial intelligence empowers digital twins in drug discovery and clinical trials
Bordukova, M., Makarov, N., Rodriguez-Esteban, R., Schmich, F., & Menden, M. P. (2024) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2023.2273839 · Cited by 235 · see citing works
High-Throughput Transcriptome Profiling in Drug and Biomarker Discovery
Yang, X., Kui, L., Tang, M., Li, D., Wei, K., Chen, W., Miao, J., & Dong, Y. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00019 · Cited by 231 · see citing works
Microfluidics-free single-cell genomics with templated emulsification
Clark, I. C., Fontanez, K. M., Meltzer, R. H., Xue, Y., Hayford, C. E., May-Zhang, A. A., D’Amato, C., Osman, A., Zhang, J. Q., Hettige, P., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01685-z · Cited by 225 · see citing works
A high-stringency blueprint of the human proteome
Adhikari, S., Nice, E. C., Deutsch, E. W., Lane, L., Omenn, G. S., Pennington, S. R., Paik, Y.-K., Overall, C. M., Corrales, F. J., Cristea, I. M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19045-9 · Cited by 210 · see citing works
Label-free chemical imaging flow cytometry by high-speed multicolor stimulated Raman scattering
Suzuki, Y., Kobayashi, K., Wakisaka, Y., Deng, D., Tanaka, S., Huang, C., Lei, C., Sun, C., Liu, H., Fujiwaki, Y., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1902322116 · Cited by 215 · see citing works
Microfluidics for Drug Development: From Synthesis to Evaluation
Liu, Y., Sun, L., Zhang, H., Shang, L., & Zhao, Y. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.0c01289 · Cited by 209 · see citing works
Organoids for Drug Discovery and Personalized Medicine
Takahashi, T. (2018) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010818-021108 · Cited by 202 · see citing works
Dou, M., Clair, G., Tsai, C., Xu, K., Chrisler, W., Sontag, R. L., Zhao, R., Moore, R. J., Liu, T., Paša‐Tolić, L., et al. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b03349 · Cited by 201 · see citing works
Experimental Considerations for Single-Cell RNA Sequencing Approaches
Nguyen, Q. H., Pervolarakis, N., Nee, K., & Kessenbrock, K. (2018) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2018.00108 · Cited by 170 · see citing works
Muraro, A., Lemanske, R. F., Castells, M., Torres, M. J., Khan, D., Simon, H.-U., Bindslev-Jensen, C., Burks, W., Poulsen, L. K., Sampson, H. A., et al. (2017) · doi:10.7892/boris.95346 · Cited by 181 · see citing works
From Protein Building Blocks to Functional Materials
Shen, Y., Levin, A., Kamada, A., Toprakcioglu, Z., Rodriguez‐Garcia, M., Xu, Y., & Knowles, T. P. J. (2021) · ACS Nano · doi:10.1021/acsnano.0c08510 · Cited by 178 · see citing works
A review on novel methodologies for drug nanoparticle preparation: Microfluidic approach
Shrimal, P., Jadeja, G. C., & Patel, S. R. (2019) · Process Safety and Environmental Protection · doi:10.1016/j.cherd.2019.11.031 · Cited by 177 · see citing works
Jackson, J. M., Witek, M. A., Kamande, J. W., & Soper, S. A. (2017) · Chemical Society Reviews · doi:10.1039/c7cs00016b · Cited by 172 · see citing works
Tavakoli, H., Zhou, W., Ma, L., Perez, S., Ibarra, A., Xu, F., Zhan, S., & Li, X. (2019) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2019.05.010 · Cited by 172 · see citing works
Wei, W., Shin, Y. S., Xue, M., Matsutani, T., Masui, K., Yang, H., Ikegami, S., Gu, Y., Herrmann, K., Johnson, D., et al. (2016) · Cancer Cell · doi:10.1016/j.ccell.2016.03.012 · Cited by 169 · see citing works
Self-citationIntelligent image-based deformation-assisted cell sorting with molecular specificity
Nawaz, A. A., Urbanska, M., Herbig, M., Nötzel, M., Kräter, M., Rosendahl, P., Herold, C., Toepfner, N., Kubánková, M., Goswami, R., et al. (2020) · Nature Methods · doi:10.1038/s41592-020-0831-y · Cited by 169 · see citing works
Enrichment and single-cell analysis of circulating tumor cells
Song, Y., Tian, T., Shi, Y., Liu, W., Zou, Y. W., Khajvand, T., Wang, S., Zhu, Z., & Yang, C. J. (2016) · Chemical Science · doi:10.1039/c6sc04671a · Cited by 167 · see citing works
Platforms for Single-Cell Collection and Analysis
Valihrach, L., Androvic, P., & Kubista, M. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19030807 · Cited by 165 · see citing works
Tsai, C., Zhao, R., Williams, S., Moore, R. J., Schultz, K., Chrisler, W., Paša‐Tolić, L., Rodland, K., Smith, R. D., Shi, T., et al. (2020) · Molecular & Cellular Proteomics · doi:10.1074/mcp.ra119.001857 · Cited by 156 · see citing works
Noninvasive detection of macrophage activation with single-cell resolution through machine learning
Pavillon, N., Hobro, A. J., Akira, S., & Smith, N. I. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1711872115 · Cited by 151 · see citing works
Multiplexed profiling of single-cell extracellular vesicles secretion
Ji, Y., Qi, D., Li, L., Su, H., Li, X., Luo, Y., Sun, B., Zhang, F., Lin, B., Liu, T., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1814348116 · Cited by 138 · see citing works
Mechanical properties of single cells: Measurement methods and applications
Hao, Y., Cheng, S., Tanaka, Y., Hosokawa, Y., Yalikun, Y., & Li, M. (2020) · Biotechnology Advances · doi:10.1016/j.biotechadv.2020.107648 · Cited by 132 · see citing works
Daguerre, H., Solsona, M., Cottet, J., Michaël Gauthier, A., Renaud, P., & Bolopion, A. (2020) · Lab on a Chip · doi:10.1039/d0lc00616e · Cited by 115 · see citing works
Bargaje, R., Trachana, K., Shelton, M. N., McGinnis, C. S., Zhou, J., Chadick, C., Cook, S. M., Cavanaugh, C., Huang, S., & Hood, L. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1621412114 · Cited by 113 · see citing works
Imaging approaches to optimize molecular therapies
Weissleder, R., Schwaiger, M. C., Gambhir, S. S., & Hricak, H. (2016) · Science Translational Medicine · doi:10.1126/scitranslmed.aaf3936 · Cited by 112 · see citing works
Circulating Tumor Cells as a Tool for Assessing Tumor Heterogeneity
Gabriel, M. T., Heymann, M., & Heymann, D. (2019) · Theranostics · doi:10.7150/thno.34337 · Cited by 111 · see citing works
Recent advances in single-cell analysis by mass spectrometry
Yin, L., Zhang, Z., Liu, Y., Gao, Y. H., & Gu, J. (2018) · The Analyst · doi:10.1039/c8an01190g · Cited by 106 · see citing works
Mukherjee, P., Nathamgari, S. S. P., Kessler, J. A., & Espinosa, H. D. (2018) · ACS Nano · doi:10.1021/acsnano.8b05473 · Cited by 107 · see citing works
Zhang, H., Liu, Y., Fields, L. G., Shi, X., Huang, P., Lu, H., Schneider, A. J., Tang, X., Puglielli, L., Welham, N. V., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-40512-6 · Cited by 108 · see citing works
Immune cell profiling in cancer: molecular approaches to cell-specific identification
Lyons, Y. A., Wu, S. Y., Overwijk, W. W., Baggerly, K., & Sood, A. K. (2017) · npj Precision Oncology · doi:10.1038/s41698-017-0031-0 · Cited by 104 · see citing works
Single-cell droplet microfluidics for biomedical applications
Liu, D., Sun, M., Zhang, J., Hu, R. H., Fu, W., Xuanyuan, T., & Liu, W. (2022) · The Analyst · doi:10.1039/d1an02321g · Cited by 108 · see citing works
An open-source solution for advanced imaging flow cytometry data analysis using machine learning
Hennig, H., Rees, P. C. T., Blasi, T., Kamentsky, L. D., Hung, J., Dao, D., Carpenter, A. E., & Filby, A. J. (2016) · Methods · doi:10.1016/j.ymeth.2016.08.018 · Cited by 103 · see citing works
Label‐Free Optofluidic Nanobiosensor Enables Real‐Time Analysis of Single‐Cell Cytokine Secretion
Li, X., Soler, M., Szydzik, C., Khoshmanesh, K., Schmidt, J., Coukos, G., Mitchell, A., & Altug, H. (2018) · Small · doi:10.1002/smll.201800698 · Cited by 102 · see citing works
Buzdin, A. A., Sorokin, M., Garazha, A., Sekacheva, M. I., Kim, E. L., Zhukov, N. V., Wang, Y., Li, X., Kar, S., Hartmann, C. J., et al. (2018) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2018.06.003 · Cited by 102 · see citing works
Su, Y., Ko, M. E., Cheng, H., Zhu, R., Xue, M., Wang, J. K., Lee, J. W., Frankiw, L. S., Xu, A. M., Wong, S. K., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15956-9 · Cited by 101 · see citing works
Self-citationSystems Pharmacology: Defining the Interactions of Drug Combinations
van Hasselt, J. G. C., & Iyengar, R. (2018) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010818-021511 · Cited by 101 · see citing works
Le, T., Aronow, R. A., Kirshtein, A., & Shahriyari, L. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa219 · Cited by 99 · see citing works
Sztilkovics, M., Gerecsei, T., Péter, B., Saftics, A., Kurunczi, S., Székács, I., Szabó, B., & Horváth, R. (2020) · Scientific Reports · doi:10.1038/s41598-019-56898-7 · Cited by 96 · see citing works
In Situ Single Cell Proteomics Reveals Circulating Tumor Cell Heterogeneity during Treatment
Khondakar, K. R., Dey, S., Wuethrich, A., Wang, J., Behren, A., Antaw, F., Wang, Y., Sina, A. A. I., & Trau, M. (2021) · ACS Nano · doi:10.1021/acsnano.0c10008 · Cited by 92 · see citing works
Su, Y., Shi, Q., & Wei, W. (2017) · PROTEOMICS · doi:10.1002/pmic.201600267 · Cited by 88 · see citing works
High Throughput Single Cell RNA Sequencing, Bioinformatics Analysis and Applications
Huang, X., Liu, S., Wu, L. L., Jiang, M., & Hou, Y. (2018) · Advances in experimental medicine and biology · doi:10.1007/978-981-13-0502-3_4 · Cited by 85 · see citing works
Quantitative Phase Imaging Flow Cytometry for Ultra‐Large‐Scale Single‐Cell Biophysical Phenotyping
Lee, K. C. M., Wang, M., Cheah, K. S. E., Chan, G., So, H. K., Wong, K. K. Y., & Tsia, K. K. (2019) · Cytometry Part A · doi:10.1002/cyto.a.23765 · Cited by 88 · see citing works
Yang, L., Chen, X.-X., Wang, L., Hu, Z., Chen, X., Hippler, M., Zhu, W., Hu, Y., Li, J., Wang, Y., et al. (2019) · Advanced Functional Materials · doi:10.1002/adfm.201905745 · Cited by 88 · see citing works
Using single‐cell multiple omics approaches to resolve tumor heterogeneity
Ortega, M. A., Poirion, O., Zhu, X., Huang, S., Wolfgruber, T. K., Sebra, R., & Garmire, L. X. (2017) · Clinical and Translational Medicine · doi:10.1186/s40169-017-0177-y · Cited by 81 · see citing works
Advancing Drug Discovery for Neurological Disorders Using iPSC-Derived Neural Organoids
Costamagna, G., Comi, G. P., & Corti, S. P. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22052659 · Cited by 89 · see citing works
EndoDB: a database of endothelial cell transcriptomics data
Khan, S., Taverna, F., Rohlenová, K., Treps, L., Geldhof, V., de Rooij, L. P. M. H., Sokol, L., Pircher, A., Conradi, L., Kalucka, J. M., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky997 · Cited by 86 · see citing works
Recent progress in lab-on-a-chip for pharmaceutical analysis and pharmacological/toxicological test
Ai, Y., Zhang, F., Wang, C., Xie, R., & Liang, Q. (2019) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2019.06.026 · Cited by 86 · see citing works
Yang, X., Mann, K. K., Wu, H., & Ding, J. (2024) · Genome biology · doi:10.1186/s13059-024-03338-z · Cited by 90 · see citing works
Single-Cell Virology: On-Chip Investigation of Viral Infection Dynamics
Guo, F., Li, S., Caglar, M. U., Mao, Z., Liu, W., Woodman, A., Arnold, J. J., Wilke, C. O., Huang, T. J., & Cameron, C. E. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.10.051 · Cited by 82 · see citing works
Apweiler, R., Beißbarth, T., Berthold, M. R., Blüthgen, N., Burmeister, Y., Dammann, O., Deutsch, A., Feuerhake, F., Franke, A., Hasenauer, J., et al. (2018) · Experimental & Molecular Medicine · doi:10.1038/emm.2017.290 · Cited by 83 · see citing works
Advancing single-cell proteomics and metabolomics with microfluidic technologies
Liu, Y., Chen, X., Zhang, Y., & Liu, J. (2018) · The Analyst · doi:10.1039/c8an01503a · Cited by 80 · see citing works
Spatial single-cell isotope tracing reveals heterogeneity of de novo fatty acid synthesis in cancer
Buglakova, E., Ekelöf, M., Schwaiger-Haber, M., Schlicker, L., Molenaar, M. R., Shahraz, M., Stuart, L., Eisenbarth, A., Hilsenstein, V., Patti, G. J., et al. (2024) · Nature Metabolism · doi:10.1038/s42255-024-01118-4 · Cited by 81 · see citing works
Microfluidic and Paper-Based Devices for Disease Detection and Diagnostic Research
Campbell, J. M., Balhoff, J. B., Landwehr, G. M., Rahman, S. M., Vaithiyanathan, M., & Melvin, A. T. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19092731 · Cited by 77 · see citing works
Current Trends of Microfluidic Single-Cell Technologies
Shinde, P., Mohan, L., Kumar, A. S., Dey, K., Maddi, A., Patananan, A. N., Tseng, F., Chang, H., Nagai, M., & Santra, T. S. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19103143 · Cited by 76 · see citing works
Liu, Q., Ge, W., Wang, T., Lan, J., Martínez‐Jarquín, S., Wolfrum, C., Stoffel, M., & Zenobi, R. (2021) · Angewandte Chemie International Edition · doi:10.1002/anie.202107223 · Cited by 75 · see citing works
Zhou, Z., Pang, Y., Ji, J., He, J., Liu, T., Ouyang, L., Zhang, W., Zhang, X., Zhang, Z., Zhang, K., et al. (2023) · Nature reviews. Immunology · doi:10.1038/s41577-023-00896-4 · Cited by 73 · see citing works
Do, T., Comi, T. J., Dunham, S. J. B., Rubakhin, S., & Sweedler, J. (2017) · Analytical Chemistry · doi:10.1021/acs.analchem.6b04819 · Cited by 67 · see citing works
Zhang, Q., Rong, Y., Yi, K., Huang, L., Chen, M., & Wang, X. (2020) · Theranostics · doi:10.7150/thno.48918 · Cited by 72 · see citing works
The impact of microfluidics in high-throughput drug-screening applications
Stefano, P. D., Bianchi, E., & Dubini, G. (2022) · Biomicrofluidics · doi:10.1063/5.0087294 · Cited by 74 · see citing works
Deep Profiling of Cellular Heterogeneity by Emerging Single‐Cell Proteomic Technologies
Yang, L., George, J., & Wang, J. (2019) · PROTEOMICS · doi:10.1002/pmic.201900226 · Cited by 70 · see citing works
Effective Soil Extraction Method for Cultivating Previously Uncultured Soil Bacteria
Nguyen, T. M., Seo, C., Ji, M., Paik, M., Myung, S., & Kim, J. (2018) · Applied and Environmental Microbiology · doi:10.1128/aem.01145-18 · Cited by 71 · see citing works
Human Pre-gastrulation Development
Wamaitha, S. E., & Niakan, K. K. (2018) · Current topics in developmental biology/Current Topics in Developmental Biology · doi:10.1016/bs.ctdb.2017.11.004 · Cited by 71 · see citing works
Scalability and Validation of Big Data Bioinformatics Software
Yang, A., Troup, M., & Ho, J. W. K. (2017) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2017.07.002 · Cited by 68 · see citing works
A systems approach to clinical oncology uses deep phenotyping to deliver personalized care
Yurkovich, J. T., Tian, Q., Price, N. D., & Hood, L. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0273-6 · Cited by 67 · see citing works
Dahmke, I. N., Verch, A., Hermannsdörfer, J., Peckys, D. B., Weatherup, R. S., Hofmann, S., & de Jonge, N. (2017) · ACS Nano · doi:10.1021/acsnano.7b05258 · Cited by 67 · see citing works
Bio‐Micromotor Tweezers for Noninvasive Bio‐Cargo Delivery and Precise Therapy
Pan, T., Shi, Y., Zhao, N., Xiong, J., Xiao, Y., Xin, H., & Li, B. (2021) · Advanced Functional Materials · doi:10.1002/adfm.202111038 · Cited by 65 · see citing works
Visualizing Single-Cell Secretion Dynamics with Single-Protein Sensitivity
McDonald, M. P., Gemeinhardt, A., König, K., Piliarik, M., Schaffer, S., Völkl, S., Aigner, M., Mackensen, A., & Sandoghdar, V. (2017) · Nano Letters · doi:10.1021/acs.nanolett.7b04494 · Cited by 65 · see citing works
Bridging the gap: microfluidic devices for short and long distance cell–cell communication
Vu, T. Q., de Castro, R. M. B., & Qin, L. (2017) · Lab on a Chip · doi:10.1039/c6lc01367h · Cited by 63 · see citing works
Leveraging premalignant biology for immune-based cancer prevention
Spira, A. E., Disis, M. L., Schiller, J. T., Vilar, E., Rebbeck, T. R., Bejar, R. L., Ideker, T. E., Arts, J., Yurgelun, M. B. B., Mesirov, J. P., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1608077113 · Cited by 63 · see citing works
A roadmap towards personalized immunology
Delhalle, S., Bode, S. F. N., Balling, R., Ollert, M. W., & HeFeng, F. Q. (2018) · npj Systems Biology and Applications · doi:10.1038/s41540-017-0045-9 · Cited by 66 · see citing works
Recent advances in cancer metabolism: a technological perspective
Kang, Y. P., Ward, N. P., & DeNicola, G. M. (2018) · Experimental & Molecular Medicine · doi:10.1038/s12276-018-0027-z · Cited by 63 · see citing works
The Making of a PreCancer Atlas: Promises, Challenges, and Opportunities
Srivastava, S., Ghosh, S., Kagan, J., Mazurchuk, R. V., Boja, E. S., Chuaqui, R. F., Chavarria-Johnson, E., Davidsen, T. M., Eary, J. F., Haim, T., et al. (2018) · Trends in cancer · doi:10.1016/j.trecan.2018.06.007 · Cited by 60 · see citing works
Balasubramani, V., Lai, X.-J., Lin, Y., Tu, H.-Y., & Cheng, C.-J. (2018) · Scientific Reports · doi:10.1038/s41598-018-24408-w · Cited by 62 · see citing works
Profiling Single Cancer Cells with Volatolomics Approach
Serasanambati, M., Broza, Y. Y., Marmur, A., & Haick, H. (2018) · iScience · doi:10.1016/j.isci.2018.12.008 · Cited by 62 · see citing works
Yue, X., Fang, X., Sun, T., Yi, J., Kuang, X., Guo, Q., Wang, Y., Gu, H., & Xu, H. T. (2022) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2022.114384 · Cited by 61 · see citing works
Cheng, X., Peng, T., Chu, T., Yang, Y., Liu, J., Gao, Q., Cao, C., & Wei, J. (2025) · Journal of Hematology & Oncology · doi:10.1186/s13045-025-01722-1 · Cited by 64 · see citing works
Plasmonic nanostructure-based bioimaging and detection techniques at the single-cell level
Lee, S., Sun, Y., Cao, Y., & Kang, S. H. (2019) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2019.05.006 · Cited by 61 · see citing works
Microchip-based single-cell functional proteomics for biomedical applications
Lu, Y., Liu, Y., Wei, W., & Shi, Q. (2017) · Lab on a Chip · doi:10.1039/c7lc00037e · Cited by 60 · see citing works
Single-Cell Protein Secretion Detection and Profiling
Chen, Z., Chen, J. J. F., & Fan, R. (2019) · Annual Review of Analytical Chemistry · doi:10.1146/annurev-anchem-061318-115055 · Cited by 60 · see citing works
ASGARD is a single-cell guided pipeline to aid repurposing of drugs
He, B., Xiao, Y., Liang, H., Huang, Q., Du, Y., Li, Y., Garmire, D., Sun, D., & Garmire, L. X. (2023) · Nature Communications · doi:10.1038/s41467-023-36637-3 · Cited by 57 · see citing works
Genetics in Atopic Dermatitis: Historical Perspective and Future Prospects
Brown, S., Elias, M. S., & Bradley, M. (2020) · Acta Dermato Venereologica · doi:10.2340/00015555-3513 · Cited by 61 · see citing works
Andjelković, U., & Josić, D. (2018) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2018.04.008 · Cited by 58 · see citing works
High-Speed Imaging Meets Single-Cell Analysis
Mikami, H., Lei, C., Nitta, N., Sugimura, T., Ito, T., Ozeki, Y., & Goda, K. (2018) · Chem · doi:10.1016/j.chempr.2018.06.011 · Cited by 56 · see citing works
Ren, Z., Liang, H., Galbo, P. M., Dharmaratne, M., Kulkarni, A. S., Fard, A. T., Aoun, M. L., Martínez-López, N., Suyama, K., Benard, O., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2107266119 · Cited by 55 · see citing works
Intracellular Hydrogen Peroxide Detection with Functionalised Nanoelectrodes
Marquitan, M., Clausmeyer, J., Actis, P., Córdoba, A. L., Korchev, Y. E., Mark, M. D., Herlitze, S., & Schuhmann, W. W. (2016) · ChemElectroChem · doi:10.1002/celc.201600390 · Cited by 55 · see citing works
Application of single-cell technology in cancer research
Liang, S.-B., & Fu, L. (2017) · Biotechnology Advances · doi:10.1016/j.biotechadv.2017.04.001 · Cited by 55 · see citing works
Single cell imaging with near‐field terahertz scanning microscopy
Li, Z., Yan, S., Zang, Z., Geng, G., Yang, Z., Li, J., Wang, L., Yao, C., Cui, H., Chang, C., et al. (2020) · Cell Proliferation · doi:10.1111/cpr.12788 · Cited by 55 · see citing works
Towards quantitative and multiplexed in vivo functional cancer genomics
Winters, I. P., Murray, C. W., & Winslow, M. M. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0053-7 · Cited by 53 · see citing works
- Authors
- Heath, J. R., Ribas, A., & Mischel, P. S.
- Affiliations
- California Institute of Technology (US)
- University of California, Los Angeles (US)
- University of California San Diego (US)
- Corresponding author
- Heath, James R.
- Venue
- Nature Reviews Drug Discovery
- Published
- 2015-12-16
- Volume
- 15
- Issue
- 3
- Pages
- 204-216
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- PMC
- PMC4883669
- OpenAlex
- W2248179576
- Cited by
- 473
- References
- 173
- Citations by year
- 2026: 13 · 2025: 28 · 2024: 30 · 2023: 51 · 2022: 39 · 2021: 43 · 2020: 56 · 2019: 61 · 2018: 75 · 2017: 56 · 2016: 20 · 2014: 1
- FWCI
- 4.88
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Reviews Drug Discovery (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (5u54ca119347-03)
- National Cancer Institute (5U54 CA119347, U54-CA119347, U54CA199090, R01CA170689)
- National Institute of Neurological Disorders and Stroke (R01NS073831)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Keywords
- single-cell analysis, drug discovery, drug development, cellular heterogeneity, single-cell genomics, single-cell transcriptomics, single-cell proteomics, multiplex proteomics, biomarkers, disease models
- MeSH terms
- Animals, Humans, Genomics, Proteomics, Drug Discovery, 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