Seventeen-colour flow cytometry: unravelling the immune system

Semiconductor Nanocrystals as Fluorescent Biological Labels

Bruchez, M. P., Moronne, M. M., Gin, P., Weiss, S., & Alivisatos, A. P. (1998) · Science · doi:10.1126/science.281.5385.2013 · Cited by 8,614

Two subsets of memory T lymphocytes with distinct homing potentials and effector functions

Sallusto, F., Lenig, D., Förster, R., Lipp, M., & Lanzavecchia, A. (1999) · Nature · doi:10.1038/44385 · Cited by 5,846

HIV preferentially infects HIV-specific CD4+ T cells

Douek, D. C., Brenchley, J. M., Betts, M. R., Ambrozak, D. R., Hill, B. J., Okamoto, Y., Casazza, J. P., Kuruppu, J. C., Kunstman, K., Wolinsky, S. M., et al. (2002) · Nature · doi:10.1038/417095a · Cited by 1,261

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

Expression of CD57 defines replicative senescence and antigen-induced apoptotic death of CD8+ T cells

Brenchley, J. M., Karandikar, N. J., Betts, M. R., Ambrozak, D. R., Hill, B. J., Crotty, L. E., Casazza, J. P., Kuruppu, J., Migueles, S. A., Connors, M., et al. (2003) · Blood · doi:10.1182/blood-2002-07-2103 · Cited by 1,073

Skewed maturation of memory HIV-specific CD8 T lymphocytes

Champagne, P., Ogg, G. S., King, A. S., Knabenhans, C., Ellefsen, K., Nobile, M., Appay, V., Rizzardi, G. P., Fleury, S., Lipp, M., et al. (2001) · Nature · doi:10.1038/35065118 · Cited by 1,002

Fluorescence Activated Cell Sorting

Bonner, W. A., Hulett, H. R., Sweet, R. G., & Herzenberg, L. A. (1972) · Review of Scientific Instruments · doi:10.1063/1.1685647 · Cited by 777

Persistent immune activation in HIV-1 infection is associated with progression to AIDS

Hazenberg, M. D., Otto, S. A., BENTHEM, B. H. B. V., Roos, M. T. L., Coutinho, R. A., Lange, J. M. A., Hamann, D., Prins, M., & Miedema, F. F. (2003) · AIDS · doi:10.1097/00002030-200309050-00006 · Cited by 764

The History and Future of the Fluorescence Activated Cell Sorter and Flow Cytometry: A View from Stanford

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

Spectral compensation for flow cytometry: Visualization artifacts, limitations, and caveats

Roederer, M. (2001) · Cytometry · doi:10.1002/1097-0320(20011101)45:3 · Cited by 561

Introduction to Multiparametric Flow Cytometry and Analysis of High-Dimensional Data

Sun, J. X., Kroeger, J. L., & Markowitz, J. (2020) · Methods in molecular biology · doi:10.1007/978-1-0716-0849-4_13 · Cited by 23

Easy performance of 6-color confocal immunofluorescence with 4-laser line microscopes

Eissing, N., Heger, L., Barańska, A., Cesnjevar, R. A., Büttner-Herold, M. J., Söder, S., Hartmann, A., Heidkamp, G. F., & Dudziak, D. (2014) · Immunology Letters · doi:10.1016/j.imlet.2014.04.003 · Cited by 18

Quasi-supervised learning for biomedical data analysis

Karaçalı, B. (2010) · Pattern Recognition · doi:10.1016/j.patcog.2010.04.024 · Cited by 18

Presence of Epstein–Barr virus-infected B lymphocytes with thyrotropin receptor antibodies on their surface in Graves’ disease patients and in healthy individuals

Nagata, K., Higaki, K., Nakayama, Y., Miyauchi, H., Kiritani, Y., Kanai, K., Matsushita, M., Iwasaki, T., Sugihara, H., Kuwamoto, S., et al. (2014) · Autoimmunity · doi:10.3109/08916934.2013.879863 · Cited by 18

Unexpected formation of (Z)-3-(halomethylene)isoindolinones from gem-dihalovinylbenzonitriles: efficient synthesis of enyne-containing isoindolinones

Wang, C., Sun, C., Weng, F., Gao, M., Liu, B., & Xu, B. (2011) · Tetrahedron Letters · doi:10.1016/j.tetlet.2011.03.143 · Cited by 18

Towards a Physiological Scale of Vocal Fold Agent-Based Models of Surgical Injury and Repair: Sensitivity Analysis, Calibration and Verification

Garg, A., Yuen, S., Seekhao, N., Yu, G., Karwowsky, J., Powell, M. D., Sakata, J. T., Mongeau, L., JáJá, J. F., & Li‐Jessen, N. Y. K. (2019) · Applied Sciences · doi:10.3390/app9152974 · Cited by 19

Flow Cytometry: A Multipurpose Technology for a Wide Spectrum of Global Biosecurity Applications

Marrone, B. L. (2009) · JALA Journal of the Association for Laboratory Automation · doi:10.1016/j.jala.2009.03.001 · Cited by 18

Application of Quantum Dots to Multicolor Flow Cytometry

Chattopadhyay, P. K., Yu, J., & Roederer, M. (2007) · Humana Press eBooks · doi:10.1385/1-59745-369-2:175 · Cited by 18

Spectral Flow Cytometry: The Current State and Future of the Technology

Astakhova, E. A., Gubaeva, A., Naumova, D. A., Egorova, A., Maznina, A. A., Rybkina, I. G., Osmanov, I. M., Tabakov, D., Mityaeva, O. N., & Volchkov, P. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26125911 · Cited by 15

A dual-labelling strategy for integrated ICPMS and LIF for the determination of peptides

Zhang, Z., Yan, X., Xu, M., Yang, L., & Wang, Q. (2011) · Journal of Analytical Atomic Spectrometry · doi:10.1039/c1ja00010a · Cited by 18

A cross-sectional study evidences regulations of leukocytes in the colostrum of mothers with obesity

Piñeiro-Salvador, R., Vázquez‐Garza, E., Cruz-Cárdenas, J. A., Licona‐Cassani, C., García‐Rivas, G., Moreno-Vásquez, J., Alcorta-García, M. R., Díaz, V. J. L., & Brunck, M. E. G. (2022) · BMC Medicine · doi:10.1186/s12916-022-02575-y · Cited by 17

Recent Advances in Cytometry Applications: Preclinical, Clinical, and Cell Biology

Mittag, A., & Tárnok, A. (2011) · Methods in cell biology · doi:10.1016/b978-0-12-385493-3.00001-2 · Cited by 17

Digital barcodes of suspension array using laser induced breakdown spectroscopy

He, Q., Liu, Y., He, Y., Zhu, L. K., Zhang, Y., & Shen, Z. (2016) · Scientific Reports · doi:10.1038/srep36511 · Cited by 17

Establishment of a flow cytometry assay for detecting paroxysmal nocturnal hemoglobinuria-type cells specific to patients with bone marrow failure

Hosokawa, K. T., Sugimori, C., Ishiyama, K., Takamatsu, H., Noji, H., Shichishima, T., Obara, N., Chiba, S., Ninomiya, H., Shirasugi, Y., et al. (2018) · Annals of Hematology · doi:10.1007/s00277-018-3443-1 · Cited by 17

PHENOTYPIC CHARACTERISATION OF PERIPHERAL BLOOD CYTOTOXIC T LYMPHOCYTES: REGULATORY AND EFFECTOR MOLECULES

Kudryavtsev, I. V., Борисов, А. Г., Vasilyeva, E., Ивановна, К. И., Савченко, А. А., Серебрякова, М. К., & Тотолян, А. А. (2018) · Medical Immunology (Russia) · doi:10.15789/1563-0625-2018-2-227-240 · Cited by 17

T hy1+ S ca1+ innate lymphoid cells infiltrate the CNS during autoimmune inflammation, but do not contribute to disease development

Mair, F., & Becher, B. (2013) · European Journal of Immunology · doi:10.1002/eji.201343653 · Cited by 17

From analog to digital models of gene regulation

Munsky, B. E., & Neuert, G. (2015) · Physical Biology · doi:10.1088/1478-3975/12/4/045004 · Cited by 17

The changing pattern of “smart” flow cytometry (S‐FC) to assist the cost‐effective diagnosis of HIV, tuberculosis, and leukemias in resource‐restricted conditions

Janossy, G. (2007) · Biotechnology Journal · doi:10.1002/biot.200700200 · Cited by 17

Plasmonic flow cytometry by immunolabeled nanorods

Crow, M. J., Marinakos, S. M., Cook, J. M., Chilkoti, A., & Wax, A. P. (2010) · Cytometry Part A · doi:10.1002/cyto.a.20994 · Cited by 16

Statistical file matching of flow cytometry data

Lee, G., Finn, W. G., & Scott, C. D. (2011) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2011.03.004 · Cited by 16

CD proteome and beyond - technologies for targeting the immune cell surfaceome

Bock, T. (2011) · Frontiers in bioscience · doi:10.2741/4006 · Cited by 16

Applying Mass Cytometry to the Analysis of Lymphoid Populations in Transplantation

Krams, S. M., Schaffert, S. A., Lau, A. H., & Martinez, O. M. (2016) · American Journal of Transplantation · doi:10.1111/ajt.14145 · Cited by 16

Simultaneous Characterization of Phospho-Proteins and Cell Cycle in Activated T Cell Subsets

Lanuti, P., Fuhrmann, S., Lachmann, R., Marchisio, M., Miscia, S., & Kern, F. (2009) · International Journal of Immunopathology and Pharmacology · doi:10.1177/039463200902200314 · Cited by 16

Ratiometric Barcoding for Mass Cytometry

Wu, X., DeGottardi, Q., Wu, I., Wu, L. J., Yu, J., Kwok, W. W., & Chiu, D. T. (2018) · Analytical Chemistry · doi:10.1021/acs.analchem.8b03201 · Cited by 16

A common genetic variant rs2821557 in KCNA3 is linked to the severity of multiple sclerosis

Lioudyno, V. I., Abdurasulova, I. N., Negoreeva, I. G., Stoliarov, I., Кудрявцев, И. В., Серебрякова, М. К., Клименко, В. М., & Lioudyno, M. (2020) · Journal of Neuroscience Research · doi:10.1002/jnr.24596 · Cited by 16

Fluorescence lifetime excitation cytometry by kinetic dithering

Li, W., Vacca, G., Castillo, M., Houston, K. D., & Houston, J. P. (2014) · Electrophoresis · doi:10.1002/elps.201300618 · Cited by 16

Stability of T cell phenotype and functional assays following heparinized umbilical cord blood collection

Scheible, K. M., Secor‐Socha, S., Wightman, T., Wang, H., Mariani, T. J., Topham, D. J., Pryhuber, G., & Quataert, S. A. (2012) · Cytometry Part A · doi:10.1002/cyto.a.22203 · Cited by 15

Nanowire array chips for molecular typing of rare trafficking leukocytes with application to neurodegenerative pathology

Kwak, M., Kim, D., Lee, M.-R., Wu, Y., Han, L. G., Lee, S., & Fan, R. (2014) · Nanoscale · doi:10.1039/c3nr06465d · Cited by 16

High throughput functional microdissection of pathogen-specific T-cell immunity using antigen and lymphocyte arrays

Pira, G. L., Ivaldi, F., Bottone, L., & Manca, F. (2007) · Journal of Immunological Methods · doi:10.1016/j.jim.2007.06.012 · Cited by 16

Antigen-Specific Gene Therapy after Immunisation Reduces the Severity of Collagen-Induced Arthritis

Eneljung, T., Tengvall, S., Jirholt, P., Henningsson, L., Holmdahl, R., Gustafsson, K. T., & Gjertsson, I. (2013) · Clinical and Developmental Immunology · doi:10.1155/2013/345092 · Cited by 16

Digital Inference of Immune Microenvironment Reveals Low-Risk Subtype of Early Lung Adenocarcinoma

Kurbatov, V., Balayev, A., Saffarzadeh, A. G., Heller, D. R., Boffa, D. J., Blasberg, J. D., Lü, J., & Khan, S. A. (2019) · The Annals of Thoracic Surgery · doi:10.1016/j.athoracsur.2019.08.050 · Cited by 16

Chemical probes for enzyme imaging: challenges in design, synthesis and biomedical applications

Nguyen, J., Zabijak, M., & Poręba, M. (2025) · Chemical Science · doi:10.1039/d5sc05683g · Cited by 19

Characterization of Thymic Development of Natural Killer T Cell Subsets by Multiparameter Flow Cytometry

Tuttle, K. D., & Gapin, L. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-7896-0_11 · Cited by 15

A New Method of Bone Stromal Cell Characterization by Flow Cytometry

Patel, C. M., Shi, L., Whitesides, J. F., Foster, B. M., Fajardo, R. J., Quillen, E. E., & Kerr, B. A. (2022) · Current Protocols · doi:10.1002/cpz1.400 · Cited by 14

Single-Cell Genomics for Investigating Pathogenesis of Inflammatory Diseases

Jung, S., & Lee, J. S. (2023) · Molecules and Cells · doi:10.14348/molcells.2023.0002 · Cited by 16

Advanced flow cytometry for biomedical applications

Pang, K., Dong, S., Zhu, Y., Zhu, X., Zhou, Q., Gu, B., Jin, W., Zhang, R., Fu, Y., Yu, B., et al. (2023) · Journal of Biophotonics · doi:10.1002/jbio.202300135 · Cited by 15

A robust pipeline for high-content, high-throughput immunophenotyping reveals age- and genetics-dependent changes in blood leukocytes

Liechti, T., Gassen, S. V., Beddall, M. H., Ballard, R. B., Iftikhar, Y., Du, R., Venkataraman, T., Novák, D., Mangino, M., Perfetto, S. P., et al. (2023) · Cell Reports Methods · doi:10.1016/j.crmeth.2023.100619 · Cited by 16

Integrated process design for single‐cell analytical technologies

Love, J. C. (2010) · AIChE Journal · doi:10.1002/aic.12413 · Cited by 15

Topology and Dynamics of Signaling Networks: In Search of Transcriptional Control of the Inflammatory Response

Androulakis, I. P., Kamisoglu, K., & Mattick, J. S. (2013) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-071812-152425 · Cited by 15

Practical Guidelines for Optimization and Characterization of the Beckman Coulter CytoFLEX™ Platform

Bhowmick, D., Sheridan, R. T. C., Bushnell, T. P., & Spalding, K. L. (2020) · Cytometry Part A · doi:10.1002/cyto.a.23998 · Cited by 15

Immature reticulocytes are sensitive and specific to low‐dose erythropoietin treatment at sea level and altitude

Jeppesen, J. S., Andersen, A. B., Bonne, T. C., Thomassen, M., Sørensen, H., Nordsborg, N. B., Olsen, N. V., Huertas, J. R., & Bejder, J. (2021) · Drug Testing and Analysis · doi:10.1002/dta.3031 · Cited by 15

Cyclic microchip assay for measurement of hundreds of functional proteins in single neurons

Yang, L., Ball, A., Liu, J. J., Jain, T., Li, Y., Akhter, F., Zhu, D., & Wang, J. (2022) · Nature Communications · doi:10.1038/s41467-022-31336-x · Cited by 14

Disease Mechanisms in Rheumatology—Tools and Pathways: Multiparameter Flow Cytometry for Discovery of Disease Mechanisms in Rheumatic Diseases

Soloski, M. J., & Chrest, F. J. (2013) · Arthritis & Rheumatism · doi:10.1002/art.37847 · Cited by 15

Toward the measurement of multiple fluorescence lifetimes in flow cytometry: maximizing multi‐harmonic content from cells and microspheres

Jenkins, P. L., Naivar, M. A., & Houston, J. P. (2015) · Journal of Biophotonics · doi:10.1002/jbio.201400115 · Cited by 15

Lectins identify distinct populations of coelomocytes in Strongylocentrotus purpuratus

Liao, W.-Y., & Fugmann, S. D. (2017) · PLoS ONE · doi:10.1371/journal.pone.0187987 · Cited by 15

Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes

Dhoble, A. S., Lahiri, P., & Bhalerao, K. D. (2018) · Journal of Biological Engineering · doi:10.1186/s13036-018-0112-9 · Cited by 15

Prototype Smartphone-Based Device for Flow Cytometry with Immunolabeling via Supra-nanoparticle Assemblies of Quantum Dots

Xiao, Z., Darwish, G. H., Susumu, K., Medintz, I. L., & Algar, W. R. (2021) · ACS Measurement Science Au · doi:10.1021/acsmeasuresciau.1c00033 · Cited by 15

“Decoding the Dots”: The ImageStream system (ISS) as a novel and powerful tool for flow cytometric analysis

Zuba‐Surma, E. K., Kucia, M., & Ratajczak, M. Z. (2007) · Open Life Sciences · doi:10.2478/s11535-007-0044-8 · Cited by 15

Predicting and controlling the reactivity of immune cell populations against cancer

Oved, K., Eden, E., Akerman, M., Noy, R., Wolchinsky, R., Izhaki, O., Schallmach, E., Kubi, A., Zabari, N., Schachter, J., et al. (2009) · Molecular Systems Biology · doi:10.1038/msb.2009.15 · Cited by 16

Sorting single T cells based on secreted cytokines and surface markers using hydrogel nanovialsPreprint

Koo, D., Dimatteo, R., Lee, S., de Rutte, J. M., & Carlo, D. D. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.28.489940 · Cited by 15

Fluorophore Multimerization as an Efficient Approach towards Bright Protein Labels

Reiber, T., Zavoiura, O., Dose, C., & Yushchenko, D. A. (2021) · European Journal of Organic Chemistry · doi:10.1002/ejoc.202100117 · Cited by 14

High-throughput Fluorescence Detections in Microfluidic Systems

Lin, S.-W., Chang, C.-H., & Lin, C. (2011) · Genomic Medicine Biomarkers and Health Sciences · doi:10.1016/s2211-4254(11)60005-8 · Cited by 14

Improved compensation of the fluorochrome AmCyan using cellular controls

DiGiuseppe, J. A., & Cardinali, J. L. (2011) · Cytometry Part B Clinical Cytometry · doi:10.1002/cyto.b.20584 · Cited by 14

Single-cell technologies for profiling T cells to enable monitoring of immunotherapies

An, X., & Varadarajan, N. (2018) · Current Opinion in Chemical Engineering · doi:10.1016/j.coche.2018.01.003 · Cited by 14

MHC‐restricted Ag85B‐specific CD8 + T cells are enhanced by recombinant BCG prime and DNA boost immunization in mice

Komine‐Aizawa, S., Jiang, J., Mizuno, S., Hayakawa, S., Matsuo, K., Boyd, L. F., Margulies, D. H., & Honda, M. (2019) · European Journal of Immunology · doi:10.1002/eji.201847988 · Cited by 14

Classification of Five Cell Types from PBMC Samples using Single Cell Transcriptomics and Artificial Neural Networks

Shaikh, R. A., Zhong, J., Lyu, M., Lin, S., Keskin, D. B., Zhang, G., Chitkushev, L. T., & Brusić, V. (2019) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm47256.2019.8983387 · Cited by 14

Genomic profile and immune contexture in colorectal cancer—relevance for prognosis and immunotherapy

Meršaková, S., Lasabová, Z., Strnádel, J., Kalman, M., Gabonova, E., Sabaka, P., Ciccocioppo, R., Rodrigo, L., Kružliak, P., & Mikolajčík, P. (2020) · Clinical and Experimental Medicine · doi:10.1007/s10238-020-00649-w · Cited by 14

The dynamic lives of T cells: new approaches and themes

Yamanaka, Y. J., Gierahn, T. M., & Love, J. C. (2012) · Trends in Immunology · doi:10.1016/j.it.2012.10.006 · Cited by 14

The Challenges for Cardiac Vascular Precursor Cell Therapy: Lessons from a Very Elusive Precursor

Roura, S., Gálvez‐Montón, C., & Bayés‐Genís, A. (2013) · Journal of Vascular Research · doi:10.1159/000353294 · Cited by 14

Enumeration of circulating fibrocytes for clinical use in asthma by an optimized single-platform flow cytometry assay

Bianchetti, L., Isgrò, M., Marini, M. A., Bellini, A., Schmidt, M., & Mattoli, S. (2014) · BBA Clinical · doi:10.1016/j.bbacli.2014.06.002 · Cited by 14

Flow: Statistics, visualization and informatics for flow cytometry

Frelinger, J., Kepler, T. B., & Chan, C. C. W. (2008) · Source Code for Biology and Medicine · doi:10.1186/1751-0473-3-10 · Cited by 14

Integrated microflow cytometry for portable immunophenotypic cell analysis

Lee, Y., Kim, B., & Choi, S. (2020) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2020.112038 · Cited by 14

Clonal Analysis of the T-Cell Response to In Vivo Expressed Mycobacterium tuberculosis Protein Rv2034, Using a CD154 Expression Based T-Cell Cloning Method

Commandeur, S., Coppola, M., Dijkman, K., Friggen, A. H., van Meijgaarden, K. E., van den Eeden, S. J. F., Wilson, L., Schip, J. J. V. D. P.-V., Franken, K. L. M. C., Geluk, A., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0099203 · Cited by 14

Lymphocyte markers and prediction of long-term renal allograft acceptance

Babel, N., Reinke, P., & Volk, H. (2009) · Current Opinion in Nephrology & Hypertension · doi:10.1097/mnh.0b013e3283318f82 · Cited by 14

Hyperspectral fluorescence microfluidic (HFM) microscopy

Caprio, G. D., Schaak, D., & Schonbrun, E. F. (2013) · Biomedical Optics Express · doi:10.1364/boe.4.001486 · Cited by 14

Metronidazole Treatment Failure and Persistent BV Lead to Increased Frequencies of Activated T- and Dendritic-Cell Subsets

Qulu, W. P., Mzobe, G. F., Mtshali, A., Letsoalo, M. P., Osman, F., San, J. E., Kama, A. O., Garrett, N., Mindel, A., Rompalo, A. M., et al. (2023) · Microorganisms · doi:10.3390/microorganisms11112643 · Cited by 12

Engineered Living Memory Microspheroid‐Based Archival File System for Random Accessible In Vivo DNA Storage

Luo, H., Huang, W. L., He, Z., Fang, Y., Tian, Y., & Xiong, Z. (2025) · Advanced Materials · doi:10.1002/adma.202415358 · Cited by 12

Multiplexed Spectral Signature Detection for Microfluidic Color-Coded Bioparticle Flow

Huang, N., Truxal, S. C., Tung, Y., Hsiao, A. Y., Luker, G. D., Takayama, S., & Kurabayashi, K. (2010) · Analytical Chemistry · doi:10.1021/ac102240g · Cited by 13

Single-cell protein secretomic signatures as potential correlates to tumor cell lineage evolution and cell–cell interaction

Kwak, M., Mu, L., Lu, Y., Chen, J. J. F., Brower, K. K., & Fan, R. (2013) · Frontiers in Oncology · doi:10.3389/fonc.2013.00010 · Cited by 13

A flow cytometric approach to analyzing mature and progenitor endothelial cells following traumatic brain injury

Assis-Nascimento, P., Umland, O., Cepero, M. L., & Liebl, D. J. (2016) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2016.01.025 · Cited by 13

HIV vaccine efficacy trials: A brief history, and options for going forward.

McKinnon, L. R., & Card, C. M. (2010) · PubMed · Cited by 13

Emerging single-cell technologies for functional proteomics in oncology

Wang, J., & Yang, F. (2016) · Expert Review of Proteomics · doi:10.1080/14789450.2016.1215920 · Cited by 13

Stand-Sit Microchip for High-Throughput, Multiplexed Analysis of Single Cancer Cells

Ramirez, L. M., Herschkowitz, J. I., & Wang, J. (2016) · Scientific Reports · doi:10.1038/srep32505 · Cited by 13

A droplet-based microfluidic flow cytometry enabling absolute quantification of single-cell proteins leveraging constriction channel

Yang, H., Wei, Y., Fan, B., Liu, L., Zhang, T., Chen, D., Wang, J., & Chen, J. (2021) · Microfluidics and Nanofluidics · doi:10.1007/s10404-021-02427-w · Cited by 13

Platelet and neutrophil responses to Porphyromonas gingivalis in human whole blood

Chen, W. A., Fletcher, H. M., Payne, K. J., Aka, S., Thornburg, M. B., Gheorghe, J. D., Safi, S. B., Shavlik, D. J., Oyoyo, U. E., & Boskovic, D. S. (2021) · Molecular Oral Microbiology · doi:10.1111/omi.12336 · Cited by 13

Label-free scattering image-spectro-microscopy for single cell and extracellular vesicle analysis

Eltigani, F. M., Zhang, X., Liu, Q., Liu, M., Peng, J., & Su, X. (2023) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2023.134572 · Cited by 13

A simulation study on superparamagnetic nanoparticle based multi-tracer tracking

Wu, K., Batra, A., Jain, S., Ye, C., Liu, J., & Wang, J. (2015) · Applied Physics Letters · doi:10.1063/1.4934743 · Cited by 13

Computational prediction of manually gated rare cells in flow cytometry data

Qiu, P. (2015) · Cytometry Part A · doi:10.1002/cyto.a.22654 · Cited by 15

A hardware accelerated system for high throughput cellular image analysis

Lee, D., Mehta, N., Shearer, A., & Kastner, R. (2017) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2017.11.013 · Cited by 13

High-throughput refractive index-based microphotonic sensor for enhanced cellular discrimination

Leblanc-Hotte, A., Chabot‐Roy, G., Odagiu, L., Richaud, M., Lesage, S., Delisle, J., & Peter, Y.-A. (2018) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2018.03.087 · Cited by 13

Flow Cytometry Data Preparation Guidelines for Improved Automated Phenotypic Analysis

Jiménez‐Carretero, D., Ligos, J. M., Martínez‐López, M., Sancho, D., & Montoya, M. C. (2018) · The Journal of Immunology · doi:10.4049/jimmunol.1800446 · Cited by 15

Immunophenotyping of Human Regulatory T Cells

Staats, J. S. (2019) · Methods in molecular biology · doi:10.1007/978-1-4939-9650-6_9 · Cited by 13

Transformation of multicolour flow cytometry data with OTflow prevents misleading multivariate analysis results and incorrect immunological conclusions

Folcarelli, R., van Staveren, S., Tinnevelt, G. H., Cadot, E., Vrisekoop, N., Buydens, L. M. C., Koenderman, L., Jansen, J. J., & van den Brink, O. F. (2021) · Cytometry Part A · doi:10.1002/cyto.a.24491 · Cited by 18

Hyperspectral Cytometry

Grégori, G., Rajwa, B. P., Patsekin, V., Jones, J. M., Furuki, M., Yamamoto, M., & Robinson, J. P. (2013) · Current topics in microbiology and immunology · doi:10.1007/82_2013_359 · Cited by 13

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Lugli, E., Troiano, L., & Cossarizza, A. (2009) · Methods in molecular biology · doi:10.1007/978-1-60327-527-9_5 · Cited by 12

Identification of organ‐specific T cell populations by analysis of multiparameter flow cytometry data using DNA‐chip analysis software

Hofmann, M., & Zerwes, H. (2006) · Cytometry Part A · doi:10.1002/cyto.a.20278 · Cited by 13

Translational sciences approach to RSV vaccine development

Kurzweil, V., Tang, R. S., Galinski, M., Wang, K., Zuo, F., Cherukuri, A., Gasser, R. A., Malkin, E. M., Sifakis, F., Mendel, D. B., et al. (2013) · Expert Review of Vaccines · doi:10.1586/14760584.2013.824706 · Cited by 13

Functional Specialization of Dendritic Cell Subsets

Heidkamp, G. F., Lehmann, C. H. K., Heger, L., Baransk, A., Hoffmann, A., Lühr, J. J., & Dudziak, D. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-394447-4.30076-1 · Cited by 13

Ultra-inert lanthanide chelates as mass tags for multiplexed bioanalysis

David, T., Šedinová, M., Myšková, A., Kuneš, J., Maletı́nská, L., Pohl, R., Dračínský, M., Mertlíková‐Kaiserová, H., Čížek, K., Klepetářová, B., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-53867-1 · Cited by 12

Current Advances in Highly Multiplexed Antibody‐Based Single‐Cell Proteomic Measurements

Huang, L., Michael, S. A., Chen, Y., & Wu, H. (2017) · Chemistry - An Asian Journal · doi:10.1002/asia.201700404 · Cited by 12

Automated flow cytometric identification of disease-specific cells by the ECLIPSE algorithm

Folcarelli, R., van Staveren, S., Bouman, R., Hilvering, B., Tinnevelt, G. H., Postma, G., van den Brink, O. F., Buydens, L. M. C., Vrisekoop, N., Koenderman, L., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-29367-w · Cited by 12

Immunological assays of hemocytes in the Northern Quahog Mercenaria mercenaria

Zeng, Y., Huo, Y., & Yang, H. (2021) · Fish & Shellfish Immunology · doi:10.1016/j.fsi.2021.09.006 · Cited by 12

Dynamic Epitope Expression from Static Cytometry Data: Principles and Reproducibility

Jacobberger, J. W., Avva, J., Sreenath, S. N., Weis, M. C., & Stefan, T. (2012) · PLoS ONE · doi:10.1371/journal.pone.0030870 · Cited by 12

Interactive, Graph-based Visual Analysis of High-dimensional, Multi-parameter Fluorescence Microscopy Data in Toponomics

Oeltze‐Jafra, S., Freiler, W., Hillert, R., Doleisch, H., Preim, B., & SCHUBERT, W. J. (2011) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2011.217 · Cited by 12

Photonic integrated circuits for multi-color laser engines

Klein, E. J., Klos, T., Witzens, J., Romero-García, S., Geuzebroek, D. H., van Kerkhof, J., Büscher, M., Krieg, J., Leisching, P., & Leuermann, J. (2017) · doi:10.1117/12.2250758 · Cited by 12

Geometry-induced injection dispersion in single-cell protein electrophoresis

Pan, Q., & Herr, A. E. (2017) · Analytica Chimica Acta · doi:10.1016/j.aca.2017.11.049 · Cited by 12

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Wiede, F., & Tiganis, T. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-7568-6_23 · Cited by 12

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Lim, S. Y., & Rizos, H. (2018) · Mammalian Genome · doi:10.1007/s00335-018-9757-4 · Cited by 12

Separation-encoded microparticles for single-cell western blotting

Gümüşcü, B., & Herr, A. E. (2019) · Lab on a Chip · doi:10.1039/c9lc00917e · Cited by 12

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Walker, E., Miller, W. L., Haley, D. P., Floyd, K., Curti, B. D., & Urba, W. J. (2009) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-08-2806 · Cited by 12

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Chattopadhyay, P. K., Högerkorp, C., & Roederer, M. (2008) · Immunology · doi:10.1111/j.1365-2567.2008.02989.x · Cited by 169

A practical approach to multicolor flow cytometry for immunophenotyping

Baumgarth, N., & Roederer, M. (2000) · Journal of Immunological Methods · doi:10.1016/s0022-1759(00)00229-5 · Cited by 451

The colorful future of cell analysis by flow cytometry.

Chattopadhyay, P. K., Perfetto, S. P., & Roederer, M. (2004) · PubMed · Cited by 11

Eleven-color flow cytometry. A powerful tool for elucidation of the complex immune system.

Rosa, S. C. D., & Roederer, M. (2001) · PubMed · Cited by 48

Investigating T Cells by Polychromatic Flow Cytometry

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