CyTOF & Helios Publications

Since the debut of CyTOF® technology in 2008, mass cytometry has catalyzed the revolution of single-cell proteomics, enabling the most comprehensive understanding of cell phenotypes, signaling pathways and function. Our complete mass cytometry system, anchored by the Helios™ instrument, combines data analysis, instrumentation, reagents and a comprehensive catalog of preconjugated antibodies to offer high-parameter single-cell protein research.

Browse our catalog of CyTOF-related publications to see how Helios and mass cytometry empower researchers to make breakthrough discoveries. Download a complete bibliography of publications.

• Overview

  Number of papers per research area as of June, 2017

  Number of cumulative papers as of June, 2017

• Recent

  • High-resolution myogenic lineage mapping by single-cell mass cytometry
    Porpiglia, E., Samusik, N., Van Ho, A.T. et al. Nature Cell Biology (2017): 558–67
  • Systems approach to uncover signaling networks in primary immunodeficiency diseases
    Choi, J., Fernandez, R., Maecker, H.T., Butte, M.J. Journal of Allergy and Clinical Immunology (2017): doi:10.1016/j.jaci.2017.03.025
  • Mass cytometry deep phenotyping of human mononuclear phagocytes and myeloid-derived suppressor cells from human blood and bone marrow
    Roussel, M., Ferrell Jr., P.B., Greenplate, A.R. et al. Journal of Leukocyte Biology (2017): doi:10.1189/jlb.5MA1116-457R
  • Combined inhibition of β-catenin and Bcr-Abl synergistically targets tyrosine kinase inhibitor-resistant blast crisis chronic myeloid leukemia blasts and progenitors in vitro and in vivo
    Zhou, H., Mak, P.Y., Mu, H. et al. Leukemia (2017): doi:10.1038/leu.2017.87
  • Human Melanoma-Derived Extracellular Vesicles Regulate Dendritic Cell Maturation
    Maus, R.L.G., Jakub, J.W., Nevala, W.K. et al. Frontiers in Immunology (2017): 358

• Research Areas

  • Biomarker Screening

    • A Frameshift in CSF2RB Predominant Among Ashkenazi Jews Increases Risk for Crohn's Disease and Reduces Monocyte Signaling via GM-CSF
      Chuang, L.S., Villaverde, N., Hui, K.Y. et al. Gastroenterology (2016): 710–23.e2
    • A time to amaze, a time to settle down, and a time to discover
      Cosma, A. Cytometry Part A (2015): 795–6
    • Cell Surface Profiling Using High-Throughput Flow Cytometry: A Platform for Biomarker Discovery and Analysis of Cellular Heterogeneity
      Gedye, C.A., Hussain, A., Paterson, J. et al. PLoS One (2014): e105602
    • A High-Sensitivity Lanthanide Nanoparticle Reporter for Mass Cytometry: Tests on Microgels as a Proxy for Cells
      Lin, W., Hou, Y., Lu, Y. et al. Langmuir (2014): 3,142–53
    • Immune cell profiling to guide therapeutic decisions in rheumatic diseases
      Ermann, J., Rao, D.A., Teslovich, N.C. et al. Nature Reviews Rheumatology (2015): 541–51
    • Signaling effects of sodium hydrosulfide in healthy donor peripheral blood mononuclear cells
      Sulen, A., Gullaksen, S.E., Bader, L. et al. Pharmacological Research (2016): 216–27
    • immunoClust—An automated analysis pipeline for the identification of immunophenotypic signatures in high-dimensional cytometric datasets
      Sörensen, T., Baumgart, S., Durek, P. et al. Cytometry, Part A (2015): 603–15
    • Single and multi-subject clustering of flow cytometry data for cell-type identification and anomaly detection
      Pouyan, M.B., Jindal, V., Birjandtalab, J., Nourani, M. BMC Medical Genomics (2016): 41
    • Bayesian Hierarchical Models for Protein Networks in Single-Cell Mass Cytometry
      Mitra, R., Müller, P., Qiu, P., Ji, Y. Cancer Informatics (2014): 79–89

  • I/O

    • An immune atlas of clear cell renal cell carcinoma
      Chevrier, S., Levine, J.H., Zanotelli, V.R.T. et al. Cell (2017): 736–49
    • Systems immune monitoring in cancer therapy
      Greenplate, A.R., Johnson, D.B., Ferrell, P.B. Jr., Irish, J.M. European Journal of Cancer (2016): 77–84
    • Combined targeting of BCL-2 and BCR-ABL tyrosine kinase eradicates chronic myeloid leukemia stem cells
      Carter, B.Z., Mak, P.Y., Mu, H. et al. Science Translational Medicine (2016): 355ra117
    • Immunodynamics: a cancer immunotherapy trials network review of immune monitoring in immuno-oncology clinical trials
      Kohrt, H.E., Tumeh, P.C., Benson, D. et al. Journal for ImmunoTherapy of Cancer (2016): 15
    • Predicting CD137 upregulation on NK cells in patients receiving monoclonal antibody therapy
      Makkouk, A., Sundaram, V., Desai, M. et al. Journal for ImmunoTherapy of Cancer (2015): P98
    • Sequential tumor and dual immune targeted immunotherapy: anti-lymphoma activity of Rituximab with 4-1bb stimulation and PD-1 blockade
      Mueller, A.M.S., Hebb, J., Sagiv-Barfi, I. et al. Journal for ImmunoTherapy of Cancer (2014): P106

  • Immunology

    • The newborn human NK cell repertoire is phenotypically formed but functionally reduced
      Strauss-Albee, D.M., Liang, E.C., Ranganath, T., et al. Cytometry Part B, Clinical Cytometry (2017): 33–41
    • Dissecting the Molecular Mechanisms of the Tropism of Varicella-Zoster Virus for Human T Cells
      Sen, N., Arvin, A.M. Journal of Virology (2016): 3,284–7
    • Single-cell technologies for monitoring immune systems
      Chattopadhyay, P.K., Gierahn, T.M., Roederer, M., Love, J.C. Nature Immunology (2014): 128–35
    • A Cell-Based Systems Biology Assessment of Human Blood to Monitor Immune Responses after Influenza Vaccination
      Hoek, K.L., Samir, P., Howard, L.M. et al. PLoS One (2015): doi:10.1371/journal.pone.0118528
    • Multiparameter analysis of stimulated human peripheral blood mononuclear cells: a comparison of mass and fluorescence cytometry
      Nicholas, K.J., Greenplate, A.R., Flaherty, D.K. et al. Cytometry Part A (2015): 271–80
    • Systemic innate immune activation in food protein-induced enterocolitis syndrome
      Goswami, R., Blazquez, A.B., Kosoy, R. et al. Journal of Allergy and Clinical Immunology (2017): doi:10.1016/j.jaci.2016.12.971
    • Regulation of adaptive NK cells and CD8 T cells by HLA-C correlates with allogeneic hematopoietic cell transplantation and with cytomegalovirus reactivation
      Horowitz, A., Guethlein, L.A., Nemat-Gorgani, N. et al. Journal of Immunology (2015): 4,524–36
    • Age‐related aspects of human IgM+ B cell heterogeneity
      Martin, V., Wu, Y.C., Kipling, D., Dunn-Walters, D.K. Annals of the New York Academy of Sciences (2015): 153–63
    • Recent progress using systems biology to better understand molecular mechanisms of immunity
      Gottschalk, R.A., Martins, A.J., Sjoelund, V. et al. Seminars in Immunology (2013): doi:10.1016/j.smim.2012.11.002
    • Implementing mass cytometry at the bedside to study the immunological basis of human diseases: distinctive immune features in patients with a history of term or preterm birth
      Gaudillière, B., Ganio, E.A., Tingle, M. et al. Cytometry, Part A (2015): 817–29
    • The interplay between Epstein-Barr virus and B lymphocytes: implications for infection, immunity, and disease
      Hatton, O.L., Arnold-Harris, A., Schaffert, S. et al. Immunologic Research (2014): 268–76
    • Mass cytometry deep phenotyping of human mononuclear phagocytes and myeloid-derived suppressor cells from human blood and bone marrow
      Roussel, M., Ferrell Jr., P.B., Greenplate, A.R. et al. Journal of Leukocyte Biology (2017): doi:10.1189/jlb.5MA1116-457R
    • Systems approach to uncover signaling networks in primary immunodeficiency diseases
      Choi, J., Fernandez, R., Maecker, H.T., Butte, M.J. Journal of Allergy and Clinical Immunology (2017): doi:10.1016/j.jaci.2017.03.025
    • Application of mass cytometry (CyTOF®) for functional and phenotypic analysis of natural killer cells
      Kay, A.W., Strauss-Albee, D.M., Blish, C.A. Methods in Molecular Biology (2016): 13–26
    • Heparin reduces nonspecific eosinophil staining artifacts in mass cytometry experiments
      Rahman, A.H., Tordesillas L., Berin M.C. Cytometry Part A (2016): 601–7
    • Single-cell states versus single-cell atlases—two classes of heterogeneity that differ in meaning and method
      Janes, K.A. Current Opinion in Biotechnology (2016): 120–5
    • Mapping the diversity of follicular helper T cells in human blood and tonsils using high-dimensional mass cytometry analysis
      Wong, M.T., Chen, J., Narayanan, S. et al. Cell Reports (2015): 1,822–33
    • Cutting Edge: Redox Signaling Hypersensitivity Distinguishes Human Germinal Center B Cells
      Polikowsky, H.G., Wogsland, C.E., Diggins, K.E. et al. Journal of Immunology (2015): 1,364–7
    • Single-cell systems-level analysis of human Toll-like receptor activation defines a chemokine signature in patients with systemic lupus erythematosus
      O'Gorman, W.E., Hsieh, E.W., Savig, E.S. et al. Journal of Allergy and Clinical Immunology (2015): 1,326–36
    • Phenotypic complexity of the human regulatory T cell compartment revealed by mass cytometry
      Mason, G.M., Lowe, K., Melchiotti, R. et al. The Journal of Immunology (2015): 2,030–7
    • A small molecule screen for enhanced homing of systemically infused cells
      Levy, O., Mortensen, L.J., Boquet, G. et al. Cell Reports (2015): 1,261–8
    • Phenotype and function of nasal dendritic cells
      Lee, H., Ruane, D., Law, K. et al. Mucosal Immunology (2015): 1,083–98
    • Beneficial Effects of CpG-Oligodeoxynucleotide Treatment on Trauma and Secondary Lung Infection
      Wanke-Jellinek, L., Keegan, J.W., Dolan, J.W. et al. The Journal of Immunology (2016): 767–77
    • Mass Cytometry of the Human Mucosal Immune System Identifies Tissue- and Disease-Associated Immune Subsets
      van Unen, V., Li, N., Molendijk, I. et al. Immunity (2016): 1,227–39
    • A High-Dimensional Atlas of Human T Cell Diversity Reveals Tissue-Specific Trafficking and Cytokine Signature
      Wong, M.T., Ong, D.E., Lim, F.S, et al. Immunity (2016): 442–56
    • Mass cytometry profiling the response of basophils and the complete peripheral blood compartment to peanut
      Tordesillas, L., Rahman, A.H., Hartmann, B.M. et al. Journal of Allergy and Clinical Immunology (2016): 1741–4.e9
    • Cytometry by time-of-flight immunophenotyping identifies a blood Sjögren's signature correlating with disease activity and glandular inflammation
      Mingueneau, M., Boudaoud, S., Haskett, S. et al. The Journal of Allergy and Clinical Immunology (2016): 1,809–21
    • Increased lymphocyte apoptosis in mouse models of colitis upon ABT-737 treatment is dependent upon BIM expression
      Lutz, C., Mozaffari, M., Tosevski, V. et al. Clinical and Experimental Immunology (2015): 343–56
    • Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum
      Bendall, S.C., Simonds, E.F., Qiu, P. et al. Science (2011): 687–96
    • Human CD4+ lymphocytes for antigen quantification: characterization using conventional flow cytometry and mass cytometry
      Wang, L., Abbasi, F., Ornatsky, O. et al. Cytometry, Part A (2012): 567–75
    • The transcriptional landscape of αβ T cell differentiation
      Mingueneau, M., Kreslavsky, T., Gray, D. et al. Nature Immunology (2013): 619–32
    • Genetic and environmental determinants of human NK cell diversity revealed by mass cytometry
      Horowitz, A., Strauss-Albee, D.M., Leipold, M. et al. Science Translational Medicine (2013): 208ra145
    • Antigen-dependent integration of opposing proximal TCR-signaling cascades determines the functional fate of T lymphocytes
      Wolchinsky, R., Hod-Marco, M., Oved, K. et al. Journal of Immunology (2014): 2,109–19
    • Clinical recovery from surgery correlates with single-cell immune signatures
      Gaudillière, B., Fragiadakis, G.K., Bruggner, R.V. et al. Science Translational Medicine (2014): 255ra131
    • Single-cell mass cytometry analysis of human tonsil T cell remodeling by varicella zoster virus
      Sen, N., Mukherjee, G., Sen, A. et al. Cell Reports (2014): 633–45
    • CD161 defines a transcriptional and functional phenotype across distinct human T cell lineages
      Fergusson, J.R., Smith, K.E., Fleming, V.M. et al. Cell Reports (2014): 1,075–88
    • Human skin is protected by four functionally and phenotypically discrete populations of resident and recirculating memory T cells
      Watanabe, R., Gehad, A., Yang, C. et al. Science Translational Medicine (2015): 279ra39
    • Pregnancy Does Not Attenuate the Antibody or Plasmablast Response to Inactivated Influenza Vaccine
      Kay, A.W., Bayless, N.L., Fukuyama, J. et al. The Journal of Infectious Diseases (2015): 861–70
    • Single-cell mass cytometry of TCR signaling: amplification of small initial differences results in low ERK activation in NOD mice.
      Mingueneau, M., Krishnaswamy, S., Spitzer, M.H. et al. Proceedings of the National Academy of Sciences (2014): 16,466–71
    • Mapping the effects of drugs on the immune system
      Kidd, B.A., Wroblewska, A., Boland, M.R. et al. Nature Biotechnology (2015): 47–54
    • Single-cell trajectory projection uncovers progression and regulatory coordination in human B cell development
      Bendall, S.C., Davis, K.L., Amir, E.D. et al. Cell (2014): 714–25
    • Adenoviral Vector Vaccination Induces a Conserved Program of CD8+ T Cell Memory Differentiation in Mouse and Man
      Bolinger, B., Sims, S., Swadling, L. et al. Cell Reports (2015): 1,578–88
    • Large-Scale and Comprehensive Immune Profiling and Functional Analysis of Normal Human Aging
      Whiting, C.C., Siebert, J., Newman, A.M. et al. PLoS One (2015): e0133627
    • Vaccinomics, adversomics, and the immune response network theory: Individualized vaccinology in the 21st century
      Poland, G.A., Kennedy, R.B., McKinney, B.A. et al. Seminars in Immunology (2013): 89–103
    • Expansion of inflammatory innate lymphoid cells in patients with common variable immune deficiency
      Cols, M., Rahman, A., Maglione, P.J. et al. Journal of Allergy and Clinical Immunology (2016): 1,206–15
    • Reversibility of Defective Hematopoiesis Caused by Telomere Shortening in Telomerase Knockout Mice
      Raval, A., Behbehani, G.K., Nguyen, L.X.T. et al. PLoS One (2015): e0131722
    • Conditional density-based analysis of T cell signaling in single-cell data
      Krishnaswamy, S., Spitzer, M.H., Mingueneau, M. et al. Science (2014): 1,250,689
    • Deep Profiling Human T Cell Heterogeneity by Mass Cytometry
      Cheng, Y., Newell, E.W. Advances in Immunology (2016): 101–34
    • Single-Cell Mass Cytometry Analysis of the Human Endocrine Pancreas
      Wang, Y.J., Golson, M.L., Schug, J., et al. Cell Metabolism (2016): 616–26
    • Expression of specific inflammasome gene modules stratifies older individuals into two extreme clinical and immunological states
      Furman, D., Chang, J., Lartigue, L. et al. Nature Medicine (2017): 174–84
    • Mass spectrometry goes with the flow: mass cytometry and its potentials in regenerative medicine
      Agnetti, G. Circulation: Cardiovascular Genetics (2012): 379–80
    • New tools for classification and monitoring of autoimmune diseases
      Maecker, H.T., Lindstrom, T.M., Robinson, W.H. et al. Nature Reviews Rheumatology (2012): 317–28
    • Human Innate Lymphoid Cell Subsets Possess Tissue-Type Based Heterogeneity in Phenotype and Frequency
      Simoni, Y., Fehlings, M., Kløverpris, H.N. et al. Immunity (2016): 148–61
    • Assessing basophil activation by using flow cytometry and mass cytometry in blood stored 24 hours before analysis
      Mukai, K., Gaudenzio, N., Gupta, S. et al. Journal of Allergy and Clinical Immunology (2016): 889–99
    • Novel tools for primary immunodeficiency diagnosis: making a case for deep profiling
      Hsieh, E.W., Hernandez, J.D. Current Opinion in Allergy and Clinical Immunology (2016): 549–56
    • The Spectrum and Regulatory Landscape of Intestinal Innate Lymphoid Cells Are Shaped by the Microbiome
      Gury-BenAri, M., Thaiss, C.A., Serafini, N. et al. Cell (2016): 1,231–46
    • Deep phenotyping of Tregs identifies an immune signature for idiopathic aplastic anemia and predicts response to treatment
      Kordasti, S., Costantini, B., Seidl, T. et al. Blood (2016): 1,193–205
    • Class I HLA haplotypes form two schools that educate NK cells in different ways
      Horowitz, A., Djaoud, Z., Nemat-Gorgani, N. et al. Science Immunology (2016): doi:10.1126/sciimmunol.aag1672
    • Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species
      Guilliams, M., Dutertre, C.A., Scott, C.L. et al. Immunity (2016): 669–84
    • Wild immunology assessed by multidimensional mass cytometry
      Japp, A.S., Hoffmann, K., Schlickeiser, S. et al. Cytometry Part A (2016): 85–95
    • Mass cytometry analytical approaches reveal cytokine-induced changes in natural killer cells
      Vendrame, E., Fukuyama, J., Strauss-Albee, D.M. et al. Cytometry Part B Clinical Cytometry (2016): 57–67
    • Comprehensive mass cytometry analysis of cell cycle, activation and coinhibitory receptors expression in CD4 T cells from healthy and HIV-infected individuals
      Corneau, A., Cosma, A., Even, S. et al. Cytometry Part B Clinical Cytometry (2016): 21–32
    • Isolation and high-dimensional phenotyping of gastrointestinal immune cells
      David, B.A., Rubino, S., Moreira, T.G. et al. Immunology (2016): 56–70
    • Lymphocyte enrichment using CD81-targeted immunoaffinity matrix
      Pelák, O., Kužílková, D., Thürner, D., et al. Cytometry Part A (2017): 62–72
    • Activation of the reward system boosts innate and adaptive immunity
      Ben-Shaanan, T.L., Azulay-Debby, H., Dubovik, T., et al. Nature Medicine (2016): 940–4
    • Impact of the microbial derived short chain fatty acid propionate on host susceptibility to bacterial and fungal infections in vivo
      Ciarlo, E., Heinonen, T., Herderschee, J. et al. Scientific Reports (2016): 37,944
    • Identification of Novel CD4+ T Cell Subsets in the Target Tissue of Sjögren’s Syndrome and Their Differential Regulation by the Lymphotoxin/LIGHT Signaling Axis
      Haskett, S., Ding, J., Zhang, W. et al. Journal of Immunology (2016): 1,600,407
    • Maturation and Phenotypic Diversity of Human CD4+ Regulatory T Cells in Umbilical Cord Blood and Peripheral Blood from Healthy Donors
      Matos, T.R., Liu, H., Hirakawa, M. et al. Blood (2015): 2,357
    • IL-2, IL-7, IL-15 and IL-6 Induce Differential Activation of Naive and Memory T Cell Subsets
      Hirakawa, M., Matos, T.R., Forcade, E. et al. Blood (2015): 3,425
    • Informatics-Based Discovery of Disease-Associated Immune Profiles
      Delmas, A., Oikonomopoulos, A., Lacey, P.N., et al. PLoS One (2016): e0163305
    • Detection, phenotyping, and quantification of antigen-specific T cells using a peptide-MHC dodecamer
      Huang, J., Zeng, X., Sigal, N., et al. Proceedings of the National Academy of Sciences of the United States of America (2016): 113
    • Systems-Level Analysis of Innate Immunity
      Zak, D.E., Tam, V.C., Aderem, A. Annual Review of Immunology (2015): 547–77
    • Technological advances transforming rheumatology
      Robinson, W.H., Mao, R. Nature Reviews Rheumatology (2015): 626–8
    • Biomarkers to guide clinical therapeutics in rheumatology?
      Robinson, W.H., Mao, R. Current Opinion in Rheumatology (2016): 168–75
    • Shooting movies of signaling network dynamics with multiparametric cytometry
      Claassen, M. Current Topics in Microbiology and Immunology (2013): 177–89
    • Different subsets of natural killer T cells may vary in their roles in health and disease
      Kumar, V., Delovitch, T.L. Immunology (2014): 321–36
    • Cracking the code of human T-cell immunity
      Harvey, C.J., Wucherpfennig, K.W. Nature Biotechnology (2013): 609–10
    • La couleur du métal Brève introduction à la cytométrie de masse (Fr.)
      Cosma, A., Le Grand, R. Médecine/sciences (2011): 1,072–4
    • Beyond model antigens: high-dimensional methods for the analysis of antigen-specific T cells
      Newell, E.W., Davis, M.M. Nature Biotechnology (2014): 149–57
    • Unifying immunology with informatics and multiscale biology
      Kidd, B.A., Peters, L.A., Schadt, E.E., Dudley, J.T. Nature Immunology (2014): 118–27
    • NK Cells in HIV Disease
      Scully, E., Alter, G. Current HIV/AIDS Reports (2016): 85–94
    • Protecting and rescuing the effectors: roles of differentiation and survival in the control of memory T cell development
      Kurtulus, S., Tripathi, P., Hildeman, D.A. Frontiers in Immunology (2013): 404
    • Systems Immunogenetics of Vaccines
      Mooney, M., McWeeney, S., Sékaly, R-P. Seminars in Immunology (2013):
    • New assays for monitoring residual HIV burden in effectively treated individuals
      Strain, M.C, Richman, D.D. Current Opinion in HIV & AIDS (2013): 106–110
    • Human NK Cell Diversity in Viral Infection: Ramifications of Ramification
      Strauss-Albee, D.M., Blish, C.A. Frontiers in Immunology (2016): 66
    • Analyzing the phenotypic and functional complexity of lymphocytes using CyTOF (cytometry by time-of-flight)
      Chen, G., Weng, N.P. Cellular and Molecular Immunology (2012): 322–3
    • Coordinated regulation of natural killer receptor expression in the maturing human immune system
      Strauss-Albee, D.M., Horowitz, A., Parham, P., Blish, C.A. Journal of Immunology (2014): 4,871–9
    • Challenges and Promise for the Development of Human Immune Monitoring
      Shen-Orr, S.S. Rambam Maimonides Medical Journal (2012): e0023
    • Higher Throughput Methods of Identifying T Cell Epitopes for Studying Outcomes of Altered Antigen Processing and Presentation
      Newell, E.W. Frontiers in Immunology (2013): 430
    • Guardians of the Gut – Murine Intestinal Macrophages and Dendritic Cells
      Gross, M., Salame, T.M., Jung, S. Frontiers in Immunology (2015): 254
    • The End: Revealing the Uniqueness of Individual Cells through the Lens of Mass Cytometry
      Bendall, S.C. Journal of Biomolecular Techniques (2013): S12

  • Immunophenotyping

    • Applying mass cytometry to the analysis of lymphoid populations in transplantation
      Krams, S.M., Schaffert, S., Lau, A.H., Martinez O.M. American Journal of Transplantation (2016): doi:10.1111/ajt.14145
    • Mass cytometry reveals a distinct immunoprofile of operational tolerance in pediatric liver transplantation
      Lau, A.H., Vitalone, M.J., Hass, K. et al. Pediatric Transplantation (2016): 1,072–80
    • Mapping the Fetomaternal Peripheral Immune System at Term Pregnancy
      Fragiadakis, G.K., Baca, Q.J., Gherardini, P.F. et al. The Journal of Immunology (2016): 4,482–92
    • The dynamic lives of T cells: new approaches and themes
      Yamanaka, Y.J., Gierahn, T.M., Love, J.C. Trends in Immunology (2013): 59–66
    • Advances in human B cell phenotypic profiling
      Kaminski, D.A., Wei, C., Qian, Y. et al. Frontiers in Immunology (2012): 302
    • Emerging single-cell technologies in immunology
      Herderschee, J., Fenwick, C., Pantaleo, G. et al. Journal of Leukocyte Biology (2015): 23–32
    • Highly multiparametric analysis by mass cytometry
      Ornatsky, O., Bandura, D., Baranov, V. et al. Journal of Immunological Methods (2010): 1–20
    • Mass cytometry: single cells, many features
      Spitzer, M.H., Nolan, G.P. Cell (2016): 780–91
    • Gliadin-specific T-cells mobilized in the peripheral blood of coeliac patients by short oral gluten challenge: clinical applications
      Picascia, S., Mandile, R., Auricchio, R. et al. Nutrients (2015): 10,020–31
    • Patient-specific immune states before surgery are strong correlates of surgical recovery
      Fragiadakis, G.K., Gaudillière, B., Ganio, E.A. et al. Anesthesiology (2015): 1,241–55
    • Mass cytometry as a platform for the discovery of cellular biomarkers to guide effective rheumatic disease therapy
      Nair, N., Mei, H.E., Chen, S.Y. et al. Arthritis Research & Therapy (2015): 127
    • An Interactive Reference Framework for Modeling a Dynamic Immune System
      Spitzer, M.H., Gherardini, P.F., Fragiadakis, G.K. et al. Science (2015): 1,259,425
    • Variation in the human immune system is largely driven by non-heritable influences.
      Brodin, P., Jojic, V., Gao, T. et al. Cell (2015): 37–47
    • Distinct immunologic changes in vivo following combination versus individual PD-1 or CTLA-4 checkpoint blockade in human cancer
      Dhodapkar, K., Verma, R., Sznol, M. et al. Journal for ImmunoTherapy of Cancer (2014): O7
    • Combination therapy with anti-CTLA4 and anti-PD1 leads to distinct immunologic changes in-vivo
      Das, R., Verma, R., Sznol, M. et al. Journal of Immunology (2015): 950–9
    • Immunomonitoring in glioma immunotherapy: Current status and future perspectives
      Lamano, J.B., Ampie, L., Choy, W. et al. Journal of Neuro-Oncology (2016): 1–13
    • Human NK cell repertoire diversity reflects immune experience and correlates with viral susceptibility
      Strauss-Albee, D.M., Fukuyama, J., Liang, E.C. et al. Science Translational Medicine (2015): 297ra115
    • Decoupling of Tumor-Initiating Activity from Stable Immunophenotype In HoxA9-Meis1 Driven AML
      Gibbs, K.D., Jager, A., Crespo, O. et al. Cell Stem Cell (2013): 210–7
    • OMIP-034: Comprehensive immune phenotyping of human peripheral leukocytes by mass cytometry for monitoring immunomodulatory therapies.
      Baumgart, S., Peddinghaus, A., Schulte-Wrede, U. et al. Cytometry Part A (2016): 34–8
    • Multicenter Systems Analysis of Human Blood Reveals Immature Neutrophils in Males and During Pregnancy
      Blazkova, J., Gupta, S., Liu, Y. et al. Journal of Immunology (2017): 2,479–88
    • Defining the Immune Microenvironment in Patients with Acute Myeloid Leukemia
      Lamble, A., Kosaka, Y., Lo, P. et al. Blood (2015): 1,374
    • Targeting YAP-dependent MDSC infiltration impairs tumor progression
      Wang, G., Lu, X., Dey, P. et al. Cancer Discovery (2016): 80–95
    • Multiparameter single cell profiling of airway inflammatory cells
      Yao, Y., Welp, T., Liu, Q. et al. Cytometry Part B, Clinical Cytometry (2016):
    • Standardizing immunophenotyping for the Human Immunology Project
      Maecker, H.T., McCoy, J.P., Nussenblatt, R. Nature Reviews Immunology (2012): 191–200
    • Immune Profiles to Predict Response to Desensitization Therapy in Highly HLA-Sensitized Kidney Transplant Candidates
      Yabu, J.M., Siebert, J.C., Maecker, H.T. PLoS One (2016): e0153355
    • Protein networks and activation of lymphocytes
      Helou, Y.A., Salomon, A.R. Current Opinion in Immunology (2015): 78–85
    • High-dimensional analysis of human CD8(+) T cell phenotype, function, and antigen specificity
      Newell, E.W., Lin, W. Current Topics in Microbiology and Immunology (2013): 61–84
    • Characterization of lung infection-induced TCRγδ T cell phenotypes by CyTOF mass cytometry
      Wanke-Jellinek, L., Keegan, J.W., Dolan, J.W., Lederer, J.A. Journal of Leukocyte Biology (2015): 483–93
    • Characterizing Phenotypes and Signaling Networks of Single Human Cells by Mass Cytometry
      Leelatian, N., Diggins, K.E., Irish, J.M. Methods in Molecular Biology (2015): 99–113
    • Categorical Analysis of Human T Cell Heterogeneity with One-Dimensional Soli-Expression by Nonlinear Stochastic Embedding
      Cheng, Y., Wong, M.T., van der Maaten, L., Newell, E.W. Journal of Immunology (2016): 924–32
    • New technologies for autoimmune disease monitoring
      Maecker, H.T., Nolan, G.P., Fathman, C.G. Current Opinion in Endocrinology, Diabetes and Obesity (2010): 322–8
    • Heterogeneity in Immune Responses – From Populations to Single Cells
      Satija, R., Shalek, A.K. Trends in Immunology (2014): 219–29
    • Interrogating the repertoire: broadening the scope of peptide–MHC multimer analysis
      Davis, M.M., Altman, J.D., Newell, E.W. Nature Reviews Immunology (2011): 551–8
    • SCREENING: CyTOF—the next generation of cell detection
      Cheung, R.K., Utz, P.J. Nature Reviews Rheumatology (2011): 502–3
    • Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE)
      Shekhar, K., Brodin, P., Davis, M.M., Chakraborty, A.K. Proceedings of the National Academy of Sciences (2014): 202–7

  • Inherited Disease

    • Dietary gluten triggers concomitant activation of CD4+ and CD8+ αβ T cells and γδ T cells in celiac disease
      Han, A., Newell, E.W., Glanville, J. et al. Proceedings of the National Academy of Sciences (2013): 13,073–8
    • Systems approaches to human autoimmune diseases
      Banchereau, R., Cepika, A.M., Pascual, V. Current Opinion in Immunology (2013): 598–605

  • Method Development

    • Next generation ligand binding assays—review of emerging technologies’ capabilities to enhance throughput and multiplexing
      Mora, J., Chunyk, A.G., Dysinger, M. et al. American Association of Pharmaceutical Scientists Journal (2014): 1,175–84
    • AutoGate: automating analysis of flow cytometry data
      Meehan, S., Walther, G., Moore, W. et al. Immunologic Research (2014): 218–23
    • COMPASS identifies T-cell subsets correlated with clinical outcomes
      Lin, L., Finak, G., Ushey, K. et al. Nature Biotechnology (2015): 610–6
    • Understanding health and disease with multidimensional single-cell methods
      Candia, J., Banavar, J.R., Losert, W. Journal of Physics: Condensed Matter (2014): 073102
    • Review of methods to probe single cell metabolism and bioenergetics
      Vasdekis, A.E., Stephanopoulos, G. Metabolic Engineering (2015): 115–35
    • The influence of PEG macromonomers on the size and properties of thermosensitive aqueous microgels
      Pich, A., Berger, S., Ornatsky, O et al. Colloid and Polymer Science (2009): 269–275
    • Hybrid nanogels by encapsulation of lanthanide-doped LaF3 nanoparticles as elemental tags for detection by atomic mass spectrometry
      Berger, S., Ornatsky, O., Baranov, V. et al. Journal of Material Chemistry (2010): 5,141–50
    • The means: Cytometry and mass spectrometry converge in a single cell deep profiling platform
      Weis-Garcia, F., Bandura, D., Baranov, V. et al. Journal of Biomolecular Techniques (2013): S12
    • Phenotyping of live human PBMC using CyTOF mass cytometry
      Leipold, M.D., Maecker, H.T. Bio-protocol (2015): e1382
    • Algorithmic tools for mining high-dimensional cytometry data
      Chester, C., Maecker, H.T. Journal of Immunology (2015): 773–9
    • Mass cytometry panel optimization through the designed distribution of signal interference
      Takahashi, C., Au-Yeung, A., Fuh, F. et al. Cytometry Part A (2016): 39–47
    • On the relationship between cell cycle analysis with ergodic principles and age-structured cell population models
      Kuritz, K., Stöhr, D., Pollak, N., Allgöwer, F. Journal of Theoretical Biology (2016): 91–102
    • Cytokine-stimulated phosphoflow of PBMC using CyTOF mass cytometry
      Fernandez, R., Maecker, H. Bio-protocol (2016): e1496
    • Meeting the challenges of measuring human immune regulation
      Martino, D., Allen, K. Journal of Immunological Methods (2015): 1–6
    • Mass cytometry moving forward in support of clinical research: advantages and considerations
      Nassar, A.F., Wisnewiski, A.V., Raddassi, K. Bioanalysis (2016): 255–7
    • Cytokine-stimulated phosphoflow of whole blood using CyTOF mass cytometry
      Fernandez, R., Maecker, H. Bio-protocol (2015): e1495
    • Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators
      Bodenmiller, B., Zunder, E.R., Finck, R. et al. Nature Biotechnology (2012): 858–67
    • Singlet gating in mass cytometry
      Lai, L., Yeo, J.G., Albani, S. Cytometry Part A (2017): 170–2
    • Exploring Glucocorticoid Receptor Agonists Mechanism of Action through Mass Cytometry and Radial Visualizations
      Abraham, Y., Gerrits, B., Ludwig, M.G. et al. Cytometry Part B Clinical Cytometry (2016): 42–56
    • Silver nanoparticles for the detection of cell surface antigens in mass cytometry
      Schulz, A.R., Stanislawiak, S., Baumgart, S. et al. Cytometry Part A (2016): doi:10.1002/cyto.a.22904
    • Optimization of mass cytometry sample cryopreservation after staining
      Sumatoh, H.R., Teng, K.W., Cheng, Y. et al. Cytometry Part A (2016): 48–61
    • Cell size assays for mass cytometry
      Stern, A.D., Rahman, A.H., Birtwhistle, M.R. Cytometry Part A (2016): 14–24
    • ICP-MS-based multiplex profiling of glycoproteins using lectins conjugated to lanthanide-chelating polymers
      Leipold, M.D., Herrera, I., Ornatsky, O. et al. Journal of Proteome Research (2008): 443–9
    • Enhanced flowType/RchyOptimyx: a BioConductor pipeline for discovery in high-dimensional cytometry data
      O'Neill, K., Jalali, A., Aghaeepour, N. et al. Bioinformatics (2014): 1,329–30
    • Bio-Functional, Lanthanide-Labeled Polymer Particles by Seeded Emulsion Polymerization and their Characterization by Novel ICP-MS Detection
      Thickett, S.C., Abdelrahman, A.I., Ornatsky, O. et al. Journal of Analytical Atomic Spectrometry (2010): 269–81
    • High-throughput quantitation of inorganic nanoparticle biodistribution at the single-cell level using mass cytometry
      Yang, Y.S., Atukorale, P.U., Moynihan, K.D. et al. Nature Communications (2017): 14,069
    • Synthetically Modified Viral Capsids as Versatile Carriers for Use in Antibody-Based Cell Targeting
      ElSohly, A.M., Netirojjanakul, C., Aanei, I.L. et al. Bioconjugate Chemistry (2015): 1590–6
    • Synthesis of a functional metal-chelating polymer and steps toward quantitative mass cytometry bioassays
      Majonis, D., Herrera, I., Ornatsky, O. et al. Analytical Chemistry (2010): 8,961–9
    • Comparison of clustering methods for high-dimensional single-cell flow and mass cytometry data
      Weber, L.M., Robinson, M.D. Cytometry Part A (2016): 1,084–96
    • Multiplexed epitope-based tissue imaging for discovery and healthcare applications
      Bodenmiller, B. Cell Systems (2016): 225–38
    • Mass cytometry: a highly multiplexed single-cell technology for advancing drug development
      Atkuri, K.R., Stevens, J.C., Neubert, H.. Drug Metabolism Disposition (2015): 227–33
    • densityCut: an efficient and versatile topological approach for automatic clustering of biological data
      Ding, J., Shah, S., Condon, A. Bioinformatics (2016): 2,567–76
    • Another step on the path to mass cytometry standardization
      Leopold, M.D. Cytometry Part A (2015): 380–2
    • Multiplexed peptide-MHC tetramer staining with mass cytometry
      Leong, M.L., Newell, E.W. Methods in Molecular Biology (2015): 115–31
    • Emerging proteomic technologies for elucidating context-dependent cellular signaling events: a big challenge of tiny proportions
      Parker, S.J., Raedschelders. K., Van Eyk, J.E. Proteomics (2015): 1,486–502
    • Characterization by mass cytometry of different methods for the preparation of muscle mononuclear cells
      Spada, F., Fuoco, C., Pirrò, S. et al. New Biotechnology (2016): 514–23
    • Highly multiplexed simultaneous detection of RNAs and proteins in single cells
      Frei, A.P., Bava, F.A., Zunder, E.R. et al. Nature Methods (2016): 269–75
    • NetworkPainter: dynamic intracellular pathway animation in Cytobank
      Karr, J.K., Guturu, H., Chen, E.Y. et al. BMC Bioinformatics (2015): 172
    • Cytometry-based single-cell analysis of intact epithelial signaling reveals MAPK activation divergent from TNF-α-induced apoptosis in vivo
      Simmons, A.J., Banerjee, A., McKinley, E.T. et al. Molecular Systems Biology (2015): 835
    • OpenCyto: An Open Source Infrastructure for Scalable, Robust, Reproducible, and Automated, End-to-End Flow Cytometry Data Analysis
      Finak, G., Frelinger, J., Jiang, W. et al. PLoS Computational Biology (2014): e1003806
    • Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm
      Zunder, E.R., Finck, R., Amir, el-A.D. et al. Nature Protocols (2015): 316–33
    • FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data
      Van Gassen, S., Callebaut, B., Van Helden, M.J. et al. Cytometry Part A (2015): 636–45
    • Computationally efficient multidimensional analysis of complex flow cytometry data using second order polynomial histograms
      Zaunders, J., Jing, J., Leipold, M. et al. Cytometry, Part A (2015): 44–58
    • Organotellurium scaffolds for mass cytometry reagent development
      Park, H., Edgar, L.J., Lumba, M.A. et al. Organic and Biomolecular Chemistry (2015): 7,027–33
    • Barcoding of live human peripheral blood mononuclear cells for multiplexed mass cytometry
      Mei, H.E., Leipold, M.D., Schulz, A.R. et al. Journal of Immunology (2015): 2,022–31
    • Evaluating the efficiency of isotope transmission for improved panel design and a comparison of the detection sensitivities of mass cytometer instruments
      Tricot, S., Meyrand, M., Sammicheli, C. et al. Cytometry, Part A (2015): 357–68
    • Identification of hypoxic cells using an organotellurium tag compatible with mass cytometry
      Edgar, L.J., Vellanki, R.N., Halupa, A. et al. Angewandte Chemie (2014): 11,473–7
    • Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry
      Giesen, C., Wang, H.A., Schapiro, D. et al. Nature Methods (2014): 417–22
    • CyTOF supports efficient detection of immune cell subsets from small samples
      Yao, Y., Liu, R., Shin, M.S. et al. Journal of Immunological Methods (2014): 1–5
    • Metal-Containing Polystyrene Beads as Standards for Mass Cytometry
      Abdelrahman, A.I., Ornatsky, O., Bandura, D. et al. Journal of Analytical Atomic Spectrometry (2010): 260–8
    • Metal-chelating polymers by anionic ring-opening polymerization and their use in quantitative mass cytometry
      Illy, N., Majonis, D., Herrera, I. et al. Biomacromolecules (2012): 2,359–69
    • A platinum-based covalent viability reagent for single-cell mass cytometry
      Fienberg, H.G., Simonds, E.F., Fantl, W.J. et al. Cytometry, Part A (2012): 467–75
    • Flow cytometer with mass spectrometer detection for massively multiplexed single-cell biomarker assay
      Tanner, S.D., Bandura, D.R., Ornatsky, O. et al. Pure and Applied Chemistry (2008): 2,627–41
    • Transient partial permeabilization with saponin enables cellular barcoding prior to surface marker staining
      Behbehani, G.K., Thom, C., Zunder, E.R. et al. Cytometry, Part A (2014): 1,011–9
    • viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia
      Amir, el-A.D., Davis, K.L., Tadmor, M.D. et al. Nature Biotechnology (2013): 545–52
    • Normalization of mass cytometry data with bead standards
      Finck, R., Simonds, E.F., Jager, A. et al. Cytometry, Part A (2013): 483–94
    • RchyOptimyx: cellular hierarchy optimization for flow cytometry
      Aghaeepour, N., Jalali, A., O'Neill, K. et al. Cytometry, Part A (2012): 1,022–30
    • Single-cell mass cytometry adapted to measurements of the cell cycle
      Behbehani, G.K., Bendall, S.C., Clutter, M.R. et al. Cytometry, Part A (2012): 552–66
    • Improving lanthanide nanocrystal colloidal stability in competitive aqueous buffer solutions using multivalent PEG-phosphonate ligands
      Cao, P., Tong, L., Hou, Y. et al. Langmuir (2012): 12,861–70
    • Effect of pendant group structure on the hydrolytic stability of polyaspartamide polymers under physiological conditions
      Lu, Y., Chau, M., Boyle, A.J. et al. Biomacromolecules (2012): 1,296–306
    • Development of mass cytometry methods for bacterial discrimination
      Leipold, M.D., Ornatsky, O., Baranov, V. et al. Analytical Biochemistry (2011): 1–8
    • Synthesis and mass cytometric analysis of lanthanide-encoded polyelectrolyte microgels
      Lin, W., Ma, X., Qian, J. et al. Langmuir (2011): 7,265–75
    • Surface Functionalization Methods to Enhance Bioconjugation in Metal-Labeled Polystyrene Particles
      Abdelrahman, A.I., Thickett, S.C., Liang, Y. et al. Macromolecules (2011): 4,801–13
    • Element-tagged immunoassay with ICP-MS detection: evaluation and comparison to conventional immunoassays
      Razumienko, E., Ornatsky, O., Kinach, R. et al. Journal of Immunological Methods (2008): 56–63
    • Development of analytical methods for multiplex bio-assay with inductively coupled plasma mass spectrometry
      Ornatsky, O.I., Kinach, R., Bandura, D.R. et al. Journal of Analytical Atomic Spectrometry (2008): 463–9
    • Critical Assessment of Automated Flow Cytometry Data Analysis Techniques
      Aghaeepour, N., Finak, G., The FlowCAP Consortium et al. Nature Methods (2013): 228–38
    • Extracting a Cellular Hierarchy from High-dimensional Cytometry Data with SPADE
      Qiu, P., Simonds, E.F., Bendall, S.C. et al. Nature Biotechnology (2011): 886–91
    • Automatic single cell segmentation on highly multiplexed tissue images
      Schüffler, P.J., Schapiro, D., Giesen, C. et al. Cytometry, Part A; (2015): 936–42
    • Biocompatible Hybrid Nanogels
      Pich, A., Zhang, F., Shen, L. et al. Small (2008): 2,171–5
    • Inductively coupled plasma mass spectrometry-based immunoassay: a review
      Liu, R., Wu, P., Yang, L. et al. Mass Spectrometry Reviews (2014): 373–93
    • Multiple cellular antigen detection by ICP-MS
      Ornatsky, O., Baranov, V.I., Bandura, D.R. et al. Journal of Immunological Methods (2006): 68–76
    • An introduction to mass cytometry: fundamentals and applications
      Tanner, S.D., Baranov, V.I., Ornatsky, O.I. et al. Cancer Immunology, Immunotherapy (2013): 955–65
    • Polymer-Based Elemental Tags for Sensitive Bioassays
      Lou, X., Zhang, G., Herrera, I. et al. Angewandte Chemie (2007): 6,111–4
    • Study of cell antigens and intracellular DNA by identification of element-containing labels and metallointercalators using inductively coupled plasma mass spectrometry
      Ornatsky, O.I., Lou, X., Nitz, M. et al. Analytical Chemistry (2008): 2,539–47
    • Lanthanide-containing polymer nanoparticles for biological tagging applications: nonspecific endocytosis and cell adhesion
      Vancaeyzeele, C., Ornatsky, O., Baranov, V. et al. Journal of the American Chemical Society (2007): 13,653–60
    • Synthesis of Uniform NaLnF4 (Ln: Sm to Ho) Nanoparticles for Mass Cytometry
      Tong, L., Lu, E., Pichaandi, J. et al. Journal of Physical Chemistry (2016): 6,269–80
    • Cluster stability in the analysis of mass cytometry data
      Melchiotti, R., Gracio, F., Kordasti, S. et al. Cytometry Part A (2017): 73–84
    • destiny: diffusion maps for large-scale single-cell data in R
      Angerer, P., Haghverdi, L., Büttner, M. et al. Bioinformatics (2016): 1,241–3
    • Single cell analysis of human tissues and solid tumors with mass cytometry
      Leelatian, N., Doxie, D.B., Greenplate, A.R. et al. Cytometry, Part B (2017): 68–78
    • Laser Ablation Inductively Coupled Plasma Mass Spectrometry
      Hutchinson, R.W., McLachlin, K.M., Riquelme, P. et al. Transplantation Direct (2015): e32
    • Barcoding of live human PBMC for multiplexed mass cytometry
      Mei, H.E., Leipold, M.D., Schulz, A.R. et al. The Journal of Immunology (2015): 2,022–31
    • Standardization and quality control for high-dimensional mass cytometry studies of human samples
      Kleinsteuber, K., Corleis, B., Rashidi, N. et al. Cytometry Part A (2016): 903–13
    • Lanthanide-containing polymer microspheres by multiple-stage dispersion polymerization for highly multiplexed bioassays
      Abdelrahman, A.I., Dai, S., Thickett, S.C. et al. Journal of the American Chemical Society (2009): 15,276–83
    • Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry
      Bandura, D.R., Baranov, V.I., Ornatsky, O.I. et al. Analytical Chemistry (2009): 6,813–22
    • Visualization and cellular hierarchy inference of single-cell data using SPADE
      Anchang, B., Hart, T.D., Bendall, S.C., et al. Nature Protocols (2016): 1,264–79
    • Automated mapping of phenotype space with single-cell data
      Samusik, N., Good, Z., Spitzer, M.H., et al. Nature Methods (2016): 493–6
    • Hybrid Imaging Labels: Providing the Link Between Mass Spectrometry-Based Molecular Pathology and Theranostics
      Buckle, T., van der Wal, S., van Malderen, S.J.M. et al. Theranostics (2017): 624–33
    • Toward deterministic and semiautomated SPADE analysis
      Qiu, P. Cytometry Part A (2017): 281–9
    • Automation of sample preparation for mass cytometry barcoding in support of clinical research: protocol optimization
      Nassar, A.F., Wisnewski, A.V., Raddassi, K. Analytical and Bioanalytical Chemistry (2017): 2,363–72
    • Distance metric learning using random forest for cytometry data
      Pouyan, M.B., Birijandtalab, J., Nourani, M. Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (2016): 2,590
    • Imaging Mass Cytometry
      Chang, Q., Ornatsky, O.I., Siddiqui, I. et al. Cytometry Part A (2017): 160–9
    • Cytofkit: A Bioconductor Package for an Integrated Mass Cytometry Data Analysis Pipeline
      Chen, H., Lau, M.C., Wong, M.T., et al. PLoS Computational Biology (2016): e1005112
    • Simultaneous determination of alpha-fetoprotein and free beta-human chorionic gonadotropin by element-tagged immunoassay with detection by inductively coupled plasma mass spectrometry
      Zhang, S., Zhang, C., Xing, Z., et al. Clinical Chemistry (2004): 1,214–21
    • Brief introduction to mass cytometry
      Cosma, A., Le Grand, R. Medecine/Sciences (2011): 1,072–4
    • Multiparameter Phenotyping of Human PBMCs Using Mass Cytometry
      Leipold, M.D., Newell, E.W., Maecker, H.T. Methods in Molecular Biology (2015): 81–95
    • Enhanced multiplexing in mass cytometry using osmium and ruthenium tetroxide species
      Catena, R., Özcan, A., Zivanovic, N., Bodenmiller, B. Cytometry Part A (2016): 491–7
    • Single-cell gene expression profiling and cell state dynamics: collecting data, correlating data points and connecting the dots
      Marr, C., Zhou, J.X., Huang, S. Current Opinion in Biotechnology (2016): 207–14
    • The potential for elemental analysis in biotechnology
      Baranov, V.I., Quinn, Z.A., Bandura, D.R., Tanner, S.D. Journal of Analytical Atomic Spectrometry (2002): 1,148–52
    • A practical guide to multiplexed mass cytometry
      Zivanovic, N., Jacobs, A., Bodenmiller, B. Current Topics in Microbiology and Immunology (2014): 95–109
    • Modeling flow cytometry data for cancer vaccine immune monitoring
      Frelinger, J., Ottinger, J., Gouttefangeas, C., Chan, C. Cancer Immunology, Immunotherapy (2010): 1,435–41
    • The numerology of T cell functional diversity
      Haining, W.N. Immunity (2012): 10–2
    • An Introduction to Automated Flow Cytometry Gating Tools and Their Implementation
      Verschoor, C.P., Lelic, A., Bramson, J.L., Bowdish, D.M.E. Frontiers in Immunology (2015): 380
    • Computational analysis of high-throughput flow cytometry data
      Robinson, J.P., Rajwa, B., Patsekin, V., Davisson, V.J. Expert Opinion on Drug Discovery (2012): 679–93
    • A Deep Profiler’s Guide to Cytometry
      Bendall, S.C., Nolan, G.P., Roederer, M., Chattopadhyay, P.K. Trends in Immunology (2012): 323–32
    • Multiplex bio-assay with inductively coupled plasma mass spectrometry: Towards a massively multivariate single-cell technology
      Tanner, S.D., Ornatsky, O., Bandura, D.R., Baranov, V.I. Spectrochimica Acta Part B: Atomic Spectroscopy (2007): 188–95
    • Development of inductively coupled plasma-mass spectrometry-based protease assays
      Lathia, U.S., Ornatsky, O., Baranov, V., Nitz, M. Analytical Biochemistry (2009): 93–8
    • Twenty (forward looking) questions
      Hassell, L.A., Wagar, E.A. Journal of Pathology Informatics (2014): 27
    • Multiplexed protease assays using element-tagged substrates
      Lathia, U.S., Ornatsky, O., Baranov, V., Nitz, M. Analytical Biochemistry (2010): 157–9
    • The synthesis and characterization of lanthanide-encoded poly(styrene-co-methacrylic acid) microspheres
      Liang, Y., Abdelrahman, A.I., Baranov, V., Winnik, M.A. Polymer (2011): 5,040–52
    • Curious results with palladium- and platinum-carrying polymers in mass cytometry bioassays and an unexpected application as a dead cell stain
      Majonis, D., Ornatsky, O., Kinach, R., Winnik, M.A. Biomacromolecules (2011): 3,997–4,010
    • Integrated inference and analysis of regulatory networks from multi-level measurements
      Poultney, C.S., Greenfield, A., Bonneau, R. Methods in Cell Biology (2012): 19–56
    • The release and extraction of lanthanide ions from metal-encoded poly (styrene-co-methacrylic acid) microspheres
      Liang, Y., Abdelrahman, A.I., Baranov, V., Winnik, M.A. Polymer (2012): 998–1,004
    • A sensitive and quantitative element-tagged immunoassay with ICPMS detection
      Baranov, V.I., Quinn, Z., Bandura, T.R., Tanner, S.D. Analytical Chemistry (2002): 1,629–36
    • Mass cytometry: protocol for daily tuning and running cell samples on a CyTOF mass cytometer
      Leipold, M.D., Maecker, H.T. Journal of Visualized Experiments (2012): e4398
    • A CD45-based barcoding approach to multiplex mass-cytometry (CyTOF)
      Lai, L., Ong, R., Li, J., Albini, S. Cytometry, Part A (2015): 369–74
    • Platinum-conjugated antibodies for application in mass cytometry
      Mei, H.E., Leipold, M.D., Maecker, H.T. Cytometry, Part A (2015): 292–300
    • Single-cell methods
      de Souza, N. Nature Methods (2012): 35
    • Analysis, Isolation, and Activation of Antigen-Specific CD4+ and CD8+ T Cells by Soluble MHC-Peptide Complexes
      Schmidt, J., Dojcinovic, D., Guillaume, P., Luescher, I. Frontiers in Immunology (2013): 218
    • Single Cell Mass Cytometry for Analysis of Immune System Functional States
      Bjornson, Z.B., Nolan, G.P., Fantl, W.J. Current Opinion in Immunology (2013): doi: 10.1016/j.coi.2013.07.004
    • Single Cell Functional Proteomics for Assessing Immune Response in Cancer Therapy: Technology, Methods, and Applications
      Ma, C., Fan, R., Elitas, M. Frontiers in Oncology (2013): 133
    • Immune monitoring technology primer: flow and mass cytometry
      Maecker, H.T., Harari, A. Journal for ImmunoTherapy of Cancer (2015): 44
    • New Advances in Cytometric Instrumentation
      Lopez, P. Journal of Biomolecular Techniques (2013): S27
    • Dual-purpose polymer labels for fluorescent and mass cytometric affinity bioassays
      Majonis, D., Ornatsky, O., Weinrich, D., Winnik, M.A. Biomacromolecules (2013): 1,503–13

  • Microbiology/Pathogen Detection (viral)

    • Identification of vaccine-altered circulating B cell phenotypes using mass cytometry and a two-step clustering analysis
      Pejoski, D., Tchitchek, N., Rodriguez, P. A. et al. The Journal of Immunology (2016): 4,814–31
    • Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes
      Newell, E.W., Sigal, N., Bendall, S.C. et al. Immunity (2012): 142–52
    • A human vaccine strategy based on chimpanzee adenoviral and MVA vectors that primes, boosts, and sustains functional HCV-specific T cell memory
      Swadling, L., Capone, S., Antrobus, R.D. et al. Science Translational Medicine (2014): 261ra153
    • Chikungunya viral arthritis in the United States: a mimic of seronegative rheumatoid arthritis
      Miner, J.J., Aw Yeang, H.X., Fox, J.M. et al. Arthritis and Rheumatology (2015): 1,214–20
    • Activation of Salmonella Typhi-Specific Regulatory T Cells in Typhoid Disease in a Wild-Type S. Typhi Challenge Model
      McArthur, M.A., Fresnay, S., Magder, L.S. et al. PLoS Pathogens (2015): e1004914
    • High-dimensional immune profiling of total and rotavirus VP6-specific intestinal and circulating B cells by mass cytometry
      Nair, N., Newell, E.W., Vollmers, C. et al. Mucosal Immunology (2015): 68–82
    • The Split Virus Influenza Vaccine rapidly activates immune cells through Fcγ receptors
      O'Gorman, W.E., Huang, H., Wei, Y.L. et al. Vaccine (2014): 5,989–97
    • Combinatorial tetramer staining and mass cytometry analysis facilitate T-cell epitope mapping and characterization
      Newell, E.W., Sigal, N., Nair, N. et al. Nature Biotechnology (2013): 623–9
    • Impact of CD4+ T Cell Responses on Clinical Outcome following Oral Administration of Wild-Type Enterotoxigenic Escherichia coli in Humans
      McArthur, M.A., Chen, W.H., Magder, L. et al. PLoS Neglected Tropical Diseases (2017): e0005291
    • The natural killer cell response to West Nile virus in young and old individuals with or without a prior history of infection
      Yao, Y., Strauss-Albee, D.M., Zhou, J.Q. et al. PLoS One (2017): e0172625
    • Role of immune aging in susceptibility to West Nile virus
      Yao, Y., Montgomery, R.R. Methods in Molecular Biology (2016): 235–47
    • Single cell mass cytometry reveals remodeling of human T cell phenotypes by varicella zoster virus
      Sen, N., Mukherjee, G., Arvin, A.M. Methods (2015): 85–94

  • Neurology

    • IL-15 superagonist/IL-15RαSushi-Fc fusion complex (IL-15SA/IL-15RαSu-Fc; ALT-803) markedly enhances specific subpopulations of NK and memory CD8+ T cells, and mediates potent anti-tumor activity against murine breast and colon carcinomas
      Kim, P.S., Kwilas, A.R., Xu, W., et al. Oncotarget (2016): 16,130–45

  • Oncology

    • Emerging understanding of multiscale tumor heterogeneity
      Gerdes, M.J., Sood, A., Sevinsky, C. et al. Frontiers in Oncology (2014): 366
    • Unraveling cell populations in tumors by single-cell mass cytometry
      Di Palma S., Bodenmiller B. Current Opinion in Biotechnology (2015): 122–9
    • Mass cytometric functional profiling of acute myeloid leukemia defines cell-cycle and immunophenotypic properties that correlate with known responses to therapy
      Behbahni, G.K., Samusik, N., Bjornson, Z.B. et al. Cancer Discovery (2015): 988–1,003
    • Mass cytometry analysis reveals hyperactive NF Kappa B signaling in myelofibrosis and secondary acute myeloid leukemia
      Fisher, D.A., Malkova, O., Engle, E.K. et al. Leukemia (2017): doi:103//leu.2016.377
    • Eradication of CML stem cells
      Carter, B.Z., Andreeff, M. Oncoscience (2016): 313–5
    • 31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016): late breaking abstracts
      Althammer, S., Steele, K., Rebelatto, M. et al. Journal for ImmunoTherapy of Cancer (2016): 91
    • Tissue resident memory T cells create genetically distinct immune microenvironments within melanoma metastasis
      Dhodapkar, K., Bar, N., Boddupalli, C.S. et al. Journal for ImmunoTherapy of Cancer (2014): O15
    • NRASG12V oncogene facilitates self-renewal in a murine model of acute myelogenous leukemia
      Sachs, Z., LaRue, R.S., Nguyen, H.T. et al. Blood (2014): 3,274–83
    • Dasatinib changes immune cell profiles concomitant with reduced tumor growth in several murine solid tumor models
      Hekim, C., Ilander, M., Yan, J. et al. Cancer Immunology Research (2017): 157–69
    • Mutant IDH1 Downregulates ATM and Alters DNA Repair and Sensitivity to DNA Damage Independent of TET2
      Inoue, S., Li, W.Y., Tseng, A. et al. Cancer Cell (2016): 337–48
    • PD-1 marks dysfunctional regulatory T cells in malignant gliomas
      Lowther, D.E., Goods, B.A., Lucca, L.E. et al. Journal of Clinical Investigation (2016): e85935
    • Single-cell measurement of the uptake, intratumoral distribution and cell cycle effects of cisplatin using mass cytometry
      Chang, Q., Ornatsky, O.I., Koch, C.J. et al. International Journal of Cancer (2015): 1202–9
    • Single-cell mass cytometry reveals intracellular survival/proliferative signaling in FLT3-ITD-mutated AML stem/progenitor cells
      Han, L., Qiu, P., Zeng, Z. et al. Cytometry, Part A (2015): 346–56
    • Mass cytometry analysis shows that a novel memory phenotype B cell is expanded in multiple myeloma
      Hansmann, L., Blum, L., Ju, C.H. et al. Cancer Immunology Research (2015): 650–60
    • Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis
      Levine, J.H., Simonds, E.F., Bendall, S.C. et al. Cell (2015): 184–97
    • Myelodysplastic Syndrome Revealed by Systems Immunology in a Melanoma Patient Undergoing Anti-PD-1 Therapy
      Greenplate, A.R., Johnson, D.B., Roussel, M. et al. Cancer Immunology Research (2016): 474–80
    • High-Dimensional Analysis of Acute Myeloid Leukemia Reveals Phenotypic Changes in Persistent Cells during Induction Therapy
      Ferrell, P.B. Jr., Diggins, K.E., Polikowsky, H.G. et al. PLoS One (2016): e0153207
    • Anti-apoptotic ARC protein confers chemoresistance by controlling leukemia-microenvironment interactions through a NFκB/IL1β signaling network
      Carter, B.Z., Mak, P.Y., Chen, Y. et al. Oncotarget (2016): 20,054–67
    • Expansion and Activation of CD103(+) Dendritic Cell Progenitors at the Tumor Site Enhances Tumor Responses to Therapeutic PD-L1 and BRAF Inhibition
      Salmon, H., Idoyaga, J., Rahman, A. et al. Immunity (2016): 924–38
    • Messenger RNA Detection in Leukemia Cell lines by Novel Metal-Tagged in situ Hybridization using Inductively Coupled Plasma Mass Spectrometry
      Ornatsky, O., Baranov, V.I., Bandura, D.R. et al. Translational Oncogenomics (2014): 1–9
    • Impaired coordination between signaling pathways is revealed in human colorectal cancer using single-cell mass cytometry of archival tissue blocks
      Simmons, A.J., Scurrah, C.R., McKinley, E.T. et al. Science Signaling (2016): rs11
    • Isotopologous Organotellurium Probes Reveal Dynamic Hypoxia In Vivo with Cellular Resolution
      Edgar, L.J., Vellanki, R.N., McKee, T.D. et al Angewandte Chemie (2016): 13,159–63
    • BET protein bromodomain inhibitor-based combinations are highly active against post-myeloproliferative neoplasm secondary AML cells
      Saenz, D.T., Fiskus, W., Manshouri, T. et al. Leukemia (2016): 678–87
    • A Prospective Clinical Trial Combining Radiation Therapy With Systemic Immunotherapy in Metastatic Melanoma
      Hiniker, S.M., Reddy, S.A., Maecker, H.T. et al. International Journal of Radiation Oncology Biology Physics (2016): 578–88
    • Novel BET protein proteolysis targeting chimera (BET-PROTAC) exerts superior lethal activity than bromodomain inhibitor (BETi) against post-myeloproliferative neoplasm (MPN) secondary (s) AML cells
      Saenz, D.T., Fiskus, W., Quian, Y. et al. Leukemia (2017): doi:10.1038/leu.2016.393
    • Mass cytometry of follicular lymphoma tumors reveals intrinsic heterogeneity in proteins including HLA-DR and a deficit in non-malignant plasmablast and germinal center B cell populations
      Wogsland, C.E., Greenplate, A.R., Kolstad, A. et al. Cytometry Part B Clinical Cytometry (2016): 79–87
    • Combined inhibition of β-catenin and Bcr-Abl synergistically targets tyrosine kinase inhibitor-resistant blast crisis chronic myeloid leukemia blasts and progenitors in vitro and in vivo
      Zhou, H., Mak, P.Y., Mu, H. et al. Leukemia (2017): doi:10.1038/leu.2017.87
    • Human Melanoma-Derived Extracellular Vesicles Regulate Dendritic Cell Maturation
      Maus, R.L.G., Jakub, J.W., Nevala, W.K. et al. Frontiers in Immunology (2017): 358
    • Interlesional diversity of T cell receptors in melanoma with immune checkpoints enriched in tissue-resident memory T cells
      Boddupalli, C.S., Bar, N., Kadaveru, K. et al. JCI Insight (2016): e88955
    • PARP inhibitor upregulates PD-L1 expression and enhances cancer-associated immunosuppression
      Jiao, S., Xia, W., Yamaguchi, H. et al. Clinical Cancer Research (2017): doi:10.1158/1078-0432.CCR-16-3215
    • Effect of cryopreservation on delineation of immune cell subpopulations in tumor specimens as determinated by multiparametric single cell mass cytometry analysis
      Kadić, E., Moniz, R.J., Huo, Y. et al. BMC Immunology (2017): 6
    • MLN0128, a novel mTOR kinase inhibitor, disrupts survival signaling and triggers apoptosis in AML and AML stem/ progenitor cells
      Zeng, Z., Wang, R.Y., Qiu, Y.H., et al. Oncotarget (2016): 55,083–97
    • Next generation metronomic chemotherapy—report from the Fifth Biennial International Metronomic and Anti-angiogenic Therapy Meeting, 6–8 May 2016, Mumbai
      Pantziarka, P., Hutchinson, L., André, N. et al. eCancer Medical Science (2016): 689
    • NCR1 Expression Identifies Canine Natural Killer Cell Subsets with Phenotypic Similarity to Human Natural Killer Cells
      Foltz, J.A., Somanchi, S.S., Yang, Y. et al. Frontiers in Immunology (2016): 521
    • Comprehensive characterization of VISTA expression in patients with acute myeloid leukemia
      Lamble, A., Kosaka, Y., Huang, F. et al. Journal of Clinical Oncology (2016): e14546
    • Perspectives in immunotherapy: meeting report from the “Immunotherapy Bridge”, Napoli, December 5th 2015
      Ascierto, P.A., Ascierto, M.L., Formenti, S. et al. Journal for ImmunoTherapy of Cancer (2016): 62
    • Cytokine-induced memory-like natural killer cells exhibit enhanced responses against myeloid leukemia
      Romee, R., Rosario, M., Berriern-Elliott, M.M., et al. Science Translational Medicine (2016): 357
    • Recent Advances in Proteomics and Cancer Biomarker Discovery
      Xiao, G.G., Recker, R.R., Deng, H-W. Clinical Medicine: Oncology (2009): 63–72
    • Quantitative Proteomics and Biomarker Discovery in Human Cancer
      Zhao, Z., Lee, W-N., P., Xiao, G.G. Expert Review of Proteomics (2009): 115–18
    • Mass Cytometry: A High-Throughput Platform to Visualize the Heterogeneity of Acute Myeloid Leukemia
      Do, P., Byrd, J.C. Cancer Discovery (2015): 912–4
    • Mass cytometry to decipher the mechanism of nongenetic drug resistance in cancer
      Fienberg, H.G., Nolan, G.P. Current Topics in Microbiology and Immunology (2014): 85–94
    • From single cells to deep phenotypes in cancer
      Bendall, S.C., Nolan, G.P. Nature Biotechnology (2012): 639–47
    • From mass cytometry to cancer prognosis
      Winter, D.R., Ledegor, G., Amit, I. Nature Biotechnology (2015): 931–2
    • Characterization of phosphorus content of biological samples by ICP-DRC-MS: potential tool for cancer research
      Bandura, D.R., Ornatsky, O.I., Liao, L. Journal of Analytical Atomic Spectrometry (2014): 96–100
    • Biochemical heterogeneity and developmental varieties in T-cell leukemia
      Chakraborty, A.K., Roose, J.P. Cell Cycle (2013): 1,480–1
    • Monitoring the Immune Competence of Cancer Patients to Predict Outcome
      Chang, S., Kohrt, H., Maecker, H.T. Cancer Immunology, Immunotherapy (2014): 713–9
    • Multiparametric Analysis of Intra-Tumoral T-Cells in Hodgkin's Lymphoma Using Mass Cytometry (CyTOF)
      Bisneto, J.V., Ansell, S.M. Blood (2015): 1,438

  • Pharmacogenomics

    • Measuring Cellular Immunity to Influenza: Methods of Detection, Applications and Challenges
      Coughlan, L., Lambe, T. Vaccines (Basel) (2015): 293–319
    • Cytometry: Measure for measure
      Kling, J. Nature (2015): 439–43
    • Pushing the frontiers of T-cell vaccines: accurate measurement of human T-cell responses
      Saade, F., Gorski, S.A., Petrovsky, N. Expert Review of Vaccines (2012): 1,459–70
    • Impact of recent innovations in the use of mass cytometry in support of drug development
      Nassar, A.F., Ogura, H., Wisnewski, A.V. Drug Discovery Today (2015): 1,169–75

  • Population Screening

    • Spatial reconstruction of single-cell gene expression
      Satija, R., Farrell, J.A., Gennert, D., Schier, A.F., Regev, A. Nature Biotechnology (2015): 495–502

  • Stem Cell

    • Proceedings: immune tolerance and stem cell transplantation: a CIRM mini-symposium and workshop report
      Talib, S., Millan, M.T., Jorgenson, R.L., Shepard, K.A. Stem Cells Translational Medicine (2015): 4–9
    • Charting a map through the cellular reprogramming landscape
      Wen, L., Tang, F. Cell Stem Cell (2016): 215–6
    • Synergistic effects of combined targeting of beta-catenin/CBP and Bcr-Abl in CML blast crisis stem/progenitor cells in vitro and in vivo as analyzed by single cell mass cytometry (CyTOF)
      Zhou, H., Mak, P.Y., Mu, H. et al. Blood (2015): 1,566
    • High-resolution myogenic lineage mapping by single-cell mass cytometry
      Porpiglia, E., Samusik, N., Van Ho, A.T. et al. Nature Cell Biology (2017): 558–67
    • A continuous molecular roadmap to iPSC reprogramming through progression analysis of single-cell mass cytometry
      Zunder, E.R., Lujan, E., Goltsev, Y. et al. Cell Stem Cell (2015): 323–37
    • Early reprogramming regulators identified by prospective isolation and mass cytometry
      Lujan, E., Zunder, E.R., Ng, Y.H. et al. Nature (2015): 352–6
    • Phosphoproteomic profiling of mouse primary HSPCs reveals new regulators of HSPC mobilization
      Wang, L.D., Ficarro, S.B., Hutchinson, J.N., et al. Blood (2016): 1,465–74
    • Cell expansion during directed differentiation of stem cells toward the hepatic lineage
      Raju, R., Chau, D., Cho, D.S. et al. Stem Cells and Development (2016): 274–84
    • Distinct signaling programs control human hematopoietic stem cell survival and proliferation
      Knapp, D.J., Hammond, C.A., Aghaeepour, N. et al. Blood (2016): 307–18
    • Combination Of Mass Cytometry and Imaging Analysis Reveals Origin, Location, and Functional Repopulation of Liver Myeloid Cells in Mice
      David, B.A., Rezende, R.M., Antunes, M.M. et al. Gastroenterology (2016): 1,176–91
    • High-dimensional analysis of the murine myeloid cell system
      Becher, B., Schlitzer, A., Chen, J. et al. Nature Immunology (2014): 1,181–9
    • Low-dose IL-2 selectively activates subsets of CD4+ Tregs and NK cells
      Hirakawa, M., Matos, T., Liu, H. et al. JCI Insight (2016): e89278
    • Studying hematopoiesis using single-cell technologies
      Ye, F., Huang, W., Guo, G. Journal of Hematology and Oncology (2017): 27

  • Other

    • Cytometry: today’s technology and tomorrow’s horizons
      Chattopadhyay, P., Roederer, M. Methods (2012): 251–8
    • Protein Ontology: a controlled structured network of protein entities
      Natale, D.A., Arighi, C.N., Blake, J.A. et al. Nucleic Acids Research (2013): D415–D421
    • Immunology. Flow cytometry, amped up
      Benoist, C., Hacohen, N. Science (2011): 677–8
    • Methods for discovery and characterization of cell subsets in high dimensional mass cytometry data
      Diggins, K.E., Ferrell, P.B. Jr., Irish, J.M. Methods (2015): 55–63
    • A mine is a terrible thing to waste: high content, single cell technologies for comprehensive immune analysis
      Chattopadhyay, P.K., Roederer, M. American Journal of Transplantation (2015): 1,155–61
    • Processing, visualising and reconstructing network models from single-cell data
      Woodhouse, S., Moignard, V., Göttgens, B., Fisher, J. Immunology and Cell Biology (2015): 256–65
    • The end of gating? An introduction to automated analysis of high dimensional cytometry data
      Mair, F., Hartmann, F.J., Mrdjen et al. European Journal of Immunology (2015): 34–43
    • Single-cell technologies are revolutionizing the approach to rare cells
      Proserpio, V., Lönnberg, T. Immunology & Cell Biology (2016): 225–9
    • Systems Biology Analysis of Heterocellular Signaling
      Tape, C.J. Trends in Biotechnology (2016): 627–37
    • SWIFT—Scalable Clustering for Automated Identification of Rare Cell Populations in Large, High-Dimensional Flow Cytometry Datasets, Part 2: Biological Evaluation
      Mosmann, T.R., Naim, I., Rebhahn, J. et al. Cytometry Plan A (2014): 422–33
    • Wishbone identifies bifurcating developmental trajectories from single-cell data
      Setty, M., Tadmor, M.D., Reich-Zeliger, S. et al. Nature Biotechnology (2016): 637–45
    • Coordinated Surgical Immune Signatures Contain Correlates of Clinical Recovery
      Gaudillière, B., Fragiadakis, G.K., Bruggner, R.V. et al. Science Translational Medicine (2014): 131
    • Computational flow cytometry: helping to make sense of high-dimensional immunology data
      Saeys, Y., Gassen, S.V., Lambrecht, B.N. Nature Reviews Immunology (2016): 449–62
    • The road ahead: Implementing mass cytometry in clinical studies, one cell at a time
      Baca, Q., Cosma, A., Nolan, G. et al. Cytometry Part B: Clinical Cytometry (2016): 10–11
    • CyTOF analysis of anti-tumor responses
      Dempsey, L.A. Nature Immunology (2017): 254
    • Conserved Regulation of p53 Network Dosage by MicroRNA–125b Occurs through Evolving miRNA–Target Gene Pairs
      Le, M.T.N., Shyh-Chang, N., Khaw, S.L. et al. PLoS Genetics (2011): e1002242
    • AirLab: a cloud-based platform to manage and share antibody-based single-cell research
      Catena, R., Özcan, A., Jacobs, A., et al. Genome Biology (2016): 142
    • On the Limitations of Biological Knowledge
      Dougherty, E.R., Shmulevich, I. Current Genomics (2012): 574–87
    • Next-generation flow cytometry
      Janes, M.R., Rommel, C. Nature Biotechnology (2011): 602–4
    • Cycling into Future: Mass Cytometry for the Cell-Cycle Analysis
      Darzynkiewicz, Z. Cytometry, Part A (2012): 546–8
    • A flow cytometry revolution
      Doerr, A. Nature Methods (2011): 531