Cyclic Immunofluorescence (CycIF), A Highly Multiplexed Method for Single‐cell Imaging
Open accessAbstract
Cyc lic I mmuno f luorescence (CycIF) is a public‐domain method for performing highly multiplexed immunofluorescence imaging using a conventional epifluorescence microscope. It uses simple reagents and existing antibodies to construct images with up to 30 channels by sequential 4‐ to 6‐channel imaging followed by fluorophore inactivation. Three variant methods are described, the most generally useful of which involves staining fixed cells with antibodies directly conjugated to Alexa Fluor dyes and imaging in four colors, inactivating fluorophores using a mild base in the presence of hydrogen peroxide and light, and then performing another round of staining and imaging. Cell morphology is preserved through multiple rounds of CycIF, and signal‐to‐noise ratios appear to increase. Unlike antibody‐stripping methods, CycIF is gentle and optimized for monolayers of cultured cells. A second protocol involves indirect immunofluorescence and a third enables chemical inactivation of genetically encoded fluorescent proteins, allowing multiplex immunofluorescence to be combined with live‐cell analysis of cells expressing fluorescent reporter proteins. © 2016 by John Wiley & Sons, Inc.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Methods such as CyCIF and 4i, which do not require proprietary instrumentation, allow elution of antibodies in relatively mild conditions that preserve sample structure up to and possibly over 20 rounds of elution and imaging, allowing detection of over 40 protein targets.
“Methods such as cyclic immunofluorescence (CyCIF)45 and iterative indirect immunofluorescence imaging (4i)46, which do not require proprietary instrumentation, allow the elution of antibodies in relatively mild conditions that preserve the sample structure up to and possibly over 20 rounds of elution and imaging, allowing the detection of over 40 protein targets.”
From Spatial mapping of cellular senescence: emerging challenges and opportunities (2023) · cites this paper as [45]
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Amir, E.-A. D., Davis, K. L., Tadmor, M. D., Simonds, E. F., Levine, J. H., Bendall, S. C., Shenfeld, D. K., Krishnaswamy, S., Nolan, G. P., & Pe'er, D. (2013) · Nature Biotechnology · doi:10.1038/nbt.2594 · Cited by 1,550 · see citing works
Multiplexed 3D cellular super-resolution imaging with DNA-PAINT and Exchange-PAINT
Jungmann, R., Avendaño, M. S., Woehrstein, J. B., Dai, M., Shih, W. M., & Yin, P. (2014) · Nature Methods · doi:10.1038/nmeth.2835 · Cited by 1,137 · see citing works
Multiplexed ion beam imaging of human breast tumors
Angelo, M., Bendall, S. C., Finck, R., Hale, M. B., Hitzman, C., Borowsky, A. D., Levenson, R. M., Lowe, J. B., Liu, S. D., Zhao, S., et al. (2014) · Nature Medicine · doi:10.1038/nm.3488 · Cited by 1,108 · see citing works
Bendall, S. C., Davis, K. L., Amir, E.-A. D., Tadmor, M. D., Simonds, E. F., Chen, T. J., Shenfeld, D. K., Nolan, G. P., & Pe’er, D. (2014) · Cell · doi:10.1016/j.cell.2014.04.005 · Cited by 906 · see citing works
Alexa Dyes, a Series of New Fluorescent Dyes that Yield Exceptionally Bright, Photostable Conjugates
Panchuk-Voloshina, N., Haugland, R. P., Bishop-Stewart, J., Bhalgat, M. K., Millard, P. J., Mao, F., Leung, W., & Haugland, R. P. (1999) · Journal of Histochemistry & Cytochemistry · doi:10.1177/002215549904700910 · Cited by 883 · see citing works
Stack, E. C., Wang, C., Roman, K., & Hoyt, C. C. (2014) · Methods · doi:10.1016/j.ymeth.2014.08.016 · Cited by 779 · see citing works
Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue
Gerdes, M. J., Sevinsky, C. J., Sood, A., Adak, S., Bello, M. O., Bordwell, A., Can, A. B., Corwin, A. D., Dinn, S. R., Filkins, R. J., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1300136110 · Cited by 733 · see citing works
Highly multiplexed imaging of single cells using a high-throughput cyclic immunofluorescence method
Lin, J., Fallahi‐Sichani, M., & Sorger, P. K. (2015) · Nature Communications · doi:10.1038/ncomms9390 · Cited by 562 · see citing works
Self-citationHigh content screening: seeing is believing
Zanella, F., Lorens, J. B., & Link, W. (2010) · Trends in biotechnology · doi:10.1016/j.tibtech.2010.02.005 · Cited by 391 · see citing works
Highly multiplexed simultaneous detection of RNAs and proteins in single cells
Frei, A. P., Bava, F.-A., Zunder, E. R., Hsieh, E. W. Y., Chen, S.-Y., Nolan, G. P., & Gherardini, P. F. (2016) · Nature Methods · doi:10.1038/nmeth.3742 · Cited by 330 · see citing works
Quantum dot imaging platform for single-cell molecular profiling
Zrazhevskiy, P., & Gao, X. (2013) · Nature Communications · doi:10.1038/ncomms2635 · Cited by 253 · see citing works
Multiple immunofluorescence labelling of formalin-fixed paraffin-embedded (FFPE) tissue
Robertson, D. M., Savage, K., Reis-Filho, J. S., & Isacke, C. M. (2008) · BMC Cell Biology · doi:10.1186/1471-2121-9-13 · Cited by 209 · see citing works
Single-cell technologies sharpen up mammalian stem cell research
Hoppe, P. S., Coutu, D. L., & Schroeder, T. (2014) · Nature Cell Biology · doi:10.1038/ncb3042 · Cited by 104 · see citing works
The Importance of Titrating Antibodies for Immunocytochemical Methods
Hoffman, G. E., Le, W. W., & Sita, L. V. (2008) · Current Protocols in Neuroscience · doi:10.1002/0471142301.ns0212s45 · Cited by 101 · see citing works
Multiplexed In Situ Immunofluorescence Using Dynamic DNA Complexes
Schweller, R. M., Zimak, J., Duose, D. Y., Qutub, A. A., Hittelman, W. N., & Diehl, M. R. (2012) · Angewandte Chemie International Edition · doi:10.1002/anie.201204304 · Cited by 66 · see citing works
The Importance of Titrating Antibodies for Immunocytochemical Methods
Hoffman, G. E., Murphy, K. J., & Sita, L. V. (2016) · Current Protocols in Neuroscience · doi:10.1002/cpns.1 · Cited by 46 · see citing works
Redefining Signaling Pathways with an Expanding Single-Cell Toolbox
Gaudet, S., & Miller‐Jensen, K. (2016) · Trends in biotechnology · doi:10.1016/j.tibtech.2016.02.009 · Cited by 41 · see citing works
Riordan, D. P., Varma, S., West, R. B., & Brown, P. O. (2015) · PLoS ONE · doi:10.1371/journal.pone.0128975 · Cited by 26 · see citing works
Donaldson, J. G. (2002) · Current Protocols in Immunology · doi:10.1002/0471142735.im2103s48 · Cited by 13 · see citing works
Health agency pulls back on 'patronizing' approach to TB treatment
Mandavilli, A. (2007) · Nature Medicine · doi:10.1038/nm0307-269 · Cited by 2 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Methods and applications for single-cell and spatial multi-omics
Vandereyken, K., Sifrim, A., Thienpont, B., & Voet, T. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00580-2 · Cited by 1,244 · see citing works
Squidpy: a scalable framework for spatial omics analysis
Palla, G., Spitzer, H., Klein, M., Fischer, D. S., Schaar, A. C., Kuemmerle, L. B., Rybakov, S., Ibarra, I. L., Holmberg, O., Virshup, I., et al. (2022) · Nature Methods · doi:10.1038/s41592-021-01358-2 · Cited by 1,125 · see citing works
He, S., Bhatt, R., Brown, C., Brown, E. A., Buhr, D. L., Chantranuvatana, K., Danaher, P., Dunaway, D., Garrison, R. G., Geiss, G., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01483-z · Cited by 814 · see citing works
Bressan, D., Battistoni, G., & Hannon, G. J. (2023) · Science · doi:10.1126/science.abq4964 · Cited by 606 · see citing works
Spatial profiling technologies illuminate the tumor microenvironment
Elhanani, O., Ben-Uri, R., & Keren, L. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.01.010 · Cited by 526 · see citing works
Keenan, A. B., Jenkins, S. L., Jagodnik, K. M., Koplev, S., He, E., Torre, D., Wang, Z., Dohlman, A. B., Silverstein, M. C., Lachmann, A., et al. (2018) · Cell Systems · doi:10.1016/j.cels.2017.11.001 · Cited by 423 · see citing works
Self-citationHigh-plex protein and whole transcriptome co-mapping at cellular resolution with spatial CITE-seq
Liu, Y., DiStasio, M., Su, G., Asashima, H., Enninful, A., Qin, X., Deng, Y., Nam, J., Gao, F., Bordignon, P., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01676-0 · Cited by 418 · see citing works
Spatial components of molecular tissue biology
Palla, G., Fischer, D. S., Regev, A., & Theis, F. J. (2022) · Nature Biotechnology · doi:10.1038/s41587-021-01182-1 · Cited by 315 · see citing works
An end-to-end workflow for multiplexed image processing and analysis
Windhager, J., Zanotelli, V. R., Schulz, D., Meyer, L., Daniel, M., Bodenmiller, B., & Eling, N. (2023) · Nature Protocols · doi:10.1038/s41596-023-00881-0 · Cited by 290 · see citing works
Mehta, A. K., Cheney, E. M., Hartl, C., Pantelidou, C., Oliwa, M., Lal, J. C., Lin, J., Hurst, K. E., Taveira, M. D. O., Johnson, N. T., et al. (2020) · Nature Cancer · doi:10.1038/s43018-020-00148-7 · Cited by 279 · see citing works
Self-citationMacrophage Biology and Mechanisms of Immune Suppression in Breast Cancer
Mehta, A., Kadel, S., Townsend, M. G., Oliwa, M., & Guerriero, J. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.643771 · Cited by 206 · see citing works
Decoding the tumor microenvironment with spatial technologies
Walsh, L. A., & Quail, D. F. (2023) · Nature Immunology · doi:10.1038/s41590-023-01678-9 · Cited by 191 · see citing works
Tumor Microenvironment Heterogeneity: Challenges and Opportunities
Runa, F., Hamalian, S., Meade, K., Shisgal, P., Gray, P. C., & Kelber, J. A. (2017) · Current Molecular Biology Reports · doi:10.1007/s40610-017-0073-7 · Cited by 178 · see citing works
Multiplex Immunohistochemistry and Immunofluorescence: A Practical Update for Pathologists
Harms, P. W., Frankel, T. L., Moutafi, M. K., Rao, A. U. K., Rimm, D. L., Taube, J. M., Thomas, D., Chan, M. P., & Pantanowitz, L. (2023) · Modern Pathology · doi:10.1016/j.modpat.2023.100197 · Cited by 178 · see citing works
Wu, Z., Trevino, A. E., Wu, E., Swanson, K., Kim, H. J., D’Angio, H. B., Preska, R., Charville, G. W., Dalerba, P. D., Egloff, A. M., et al. (2022) · Nature Biomedical Engineering · doi:10.1038/s41551-022-00951-w · Cited by 154 · see citing works
Spatial mapping of cellular senescence: emerging challenges and opportunities
Gurkar, A. U., Gerencser, A. A., Mora, A. L., Nelson, A. C., Zhang, A. R., Lagnado, A. B., Enninful, A., Benz, C., Furman, D., Beaulieu, D., et al. (2023) · Nature Aging · doi:10.1038/s43587-023-00446-6 · Cited by 139 · see citing works
Coy, S., Rashid, R., Lin, J., Du, Z., Donson, A. M., Hankinson, T. C., Foreman, N. K., Manley, P. E., Kieran, M. W., Reardon, D. A., et al. (2018) · Neuro-Oncology · doi:10.1093/neuonc/noy035 · Cited by 105 · see citing works
Self-citationMultiplex Immunofluorescence: A Powerful Tool in Cancer Immunotherapy
Sheng, W., Zhang, C., Mohiuddin, T. M., Al-Rawe, M., Zeppernick, F. A., Falcone, F. H., Meinhold-Heerlein, I. M., & Hussain, A. F. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24043086 · Cited by 93 · see citing works
Bender, C., Calvo, T. R., Amirian, N., Coppieters, K. T., & von Herrath, M. G. (2020) · Science Advances · doi:10.1126/sciadv.abc5586 · Cited by 91 · see citing works
Emerging approaches to study cell-cell interactions in tumor microenvironment
Nishida‐Aoki, N., & Gujral, T. S. (2019) · Oncotarget · doi:10.18632/oncotarget.26585 · Cited by 75 · see citing works
High-plex Multiomic Analysis in FFPE at Subcellular Level by Spatial Molecular ImagingPreprint
He, S., Bhatt, R., Brown, C., Brown, E., Buhr, D. L., Chantranuvatana, K., Danaher, P. J., Dunaway, D. L., Garrison, R. G., Geiss, G. K., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.03.467020 · Cited by 72 · see citing works
Lee, Y. K., Lee, M., Shin, Y., Kim, K., & Kim, T. J. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26093949 · Cited by 75 · see citing works
Burlingame, E. A., McDonnell, M., Schau, G. F., Thibault, G., Lanciault, C., Morgan, T. K., Johnson, B., Corless, C. L., Gray, J. W., & Chang, Y. H. (2020) · Scientific Reports · doi:10.1038/s41598-020-74500-3 · Cited by 63 · see citing works
Baquer, G., Sementé, L., Mahamdi, T., Correig, X., Ràfols, P., & García‐Altares, M. (2022) · Mass Spectrometry Reviews · doi:10.1002/mas.21794 · Cited by 66 · see citing works
Squidpy: a scalable framework for spatial single cell analysisPreprint
Palla, G., Spitzer, H., Klein, M., Fischer, D. S., Schaar, A. C., Kuemmerle, L. B., Rybakov, S., Ibarra, I. L., Holmberg, O., Virshup, I., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.19.431994 · Cited by 61 · see citing works
Kuswanto, W. F., Nolan, G. P., & Lu, G. (2022) · Seminars in Immunopathology · doi:10.1007/s00281-022-00974-0 · Cited by 59 · see citing works
Krueger, R., Beyer, J., Jang, W.-D., Kim, N. W., Sokolov, A., Sorger, P. K., & Pfister, H. (2019) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2019.2934547 · Cited by 58 · see citing works
Self-citationSpatially Resolved Single-Cell Omics: Methods, Challenges, and Future Perspectives
Dezem, F. S., Arjumand, W., DuBose, H., Morosini, N. S., & Plummer, J. (2024) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-102523-103640 · Cited by 59 · see citing works
Connectivity Mapping: Methods and Applications
Keenan, A. B., Wojciechowicz, M. L., Wang, Z., Jagodnik, K. M., Jenkins, S. L., Lachmann, A., & Ma’ayan, A. (2019) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-072018-021211 · Cited by 57 · see citing works
Keenan, T. E., Li, T., Vallius, T., Guerriero, J. L., Tayob, N., Kochupurakkal, B. S., Davis, J. A., Pastorello, R., Tahara, R. K., Anderson, L., et al. (2020) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-20-3089 · Cited by 54 · see citing works
Self-citationTernes, L., Dane, M. A., Gross, S. M., Labrie, M., Mills, G. B., Gray, J. W., Heiser, L. M., & Chang, Y. H. (2022) · Communications Biology · doi:10.1038/s42003-022-03218-x · Cited by 51 · see citing works
Bortolomeazzi, M., Montorsi, L., Temelkovski, D., Keddar, M. R., Acha‐Sagredo, A., Pitcher, M. J., Basso, G., Laghi, L., Rodriguez‐Justo, M., Spencer, J., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28470-x · Cited by 46 · see citing works
Sheng, C., Mendler, I.-H., Rieke, S., Snyder, P., Jentsch, M., Friedrich, D., Drossel, B., & Loewer, A. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.03.031 · Cited by 45 · see citing works
Adoptive T Cell Therapy: New Avenues Leading to Safe Targets and Powerful Allies
Hammerl, D., Rieder, D., Martens, J. W. M., Trajanoski, Z., & Debets, R. (2018) · Trends in Immunology · doi:10.1016/j.it.2018.09.004 · Cited by 42 · see citing works
Muñoz-Castro, C., Noori, A., Magdamo, C. G., Li, Z., Marks, J. D., Frosch, M. P., Das, S., Hyman, B. T., & Serrano-Pozo, A. (2022) · Journal of Neuroinflammation · doi:10.1186/s12974-022-02383-4 · Cited by 41 · see citing works
Estimation methods for heterogeneous cell population models in systems biology
Waldherr, S. (2018) · Journal of The Royal Society Interface · doi:10.1098/rsif.2018.0530 · Cited by 36 · see citing works
Chen, E., Ling, A. L., Reardon, D. A., & Chiocca, E. A. (2023) · Neuro-Oncology · doi:10.1093/neuonc/noad211 · Cited by 38 · see citing works
Mi, H., Sivagnanam, S., Ho, W. J., Zhang, S., Bergman, D. R., Deshpande, A. M., Baras, A. S., Jaffee, E. M., Coussens, L. M., Fertig, E. J., et al. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae421 · Cited by 38 · see citing works
Oligonucleotide conjugated antibody strategies for cyclic immunostaining
Jones, J. A., McMahon, N. P., Zheng, T., Eng, J. R., Chin, K., Kwon, S., Nederlof, M. A., Gray, J. W., & Gibbs, S. L. (2021) · Scientific Reports · doi:10.1038/s41598-021-03135-9 · Cited by 38 · see citing works
Developmental basis of SHH medulloblastoma heterogeneity
Gold, M. P., Ong, W., Masteller, A. M., Ghasemi, D. R., Galindo, J., Park, N. R., Huynh, N. C., Donde, A., Pister, V. I., Saurez, R. A., et al. (2024) · Nature Communications · doi:10.1038/s41467-023-44300-0 · Cited by 36 · see citing works
Gross, S. M., Dane, M. A., Smith, R. L., Devlin, K. L., McLean, I. C., Derrick, D. S., Mills, C. E., Subramanian, K., London, A. B., Torre, D., et al. (2022) · Communications Biology · doi:10.1038/s42003-022-03975-9 · Cited by 35 · see citing works
Self-citationSingle-Cell Multi-Omics: Insights into Therapeutic Innovations to Advance Treatment in Cancer
Guan, A., & Quek, C. Y. J. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26062447 · Cited by 32 · see citing works
Overview of Tissue Imaging Methods
Patel, S. S., & Rodig, S. J. (2019) · Methods in molecular biology · doi:10.1007/978-1-4939-9773-2_21 · Cited by 32 · see citing works
McMahon, N. P., Jones, J. A., Kwon, S., Chin, K., Nederlof, M. A., Gray, J. W., & Gibbs, S. L. (2020) · Journal of Biomedical Optics · doi:10.1117/1.jbo.25.5.056004 · Cited by 30 · see citing works
Labrie, M., Li, A., Creason, A., Betts, C. B., Keck, J. M., Johnson, B., Sivagnanam, S., Boniface, C. T., Ma, H., Blucher, A., et al. (2021) · npj Precision Oncology · doi:10.1038/s41698-021-00232-w · Cited by 29 · see citing works
Antigen reactivity defines tissue-resident memory and exhausted T cells in tumors
Burn, T. N., Schröder, J., Gandolfo, L. C., Osman, M., Wainwright, E. N., Lam, E. Y. N., McDonald, K. M., Evans, R., Li, S., Rawlinson, D., et al. (2025) · Nature Immunology · doi:10.1038/s41590-025-02347-9 · Cited by 32 · see citing works
Self-citationIn Vivo Click Chemistry Enables Multiplexed Intravital Microscopy
Ko, J., Lucas, K., Köhler, R. H., Halabi, E. A., Wilkovitsch, M., Carlson, J., & Weissleder, R. (2022) · Advanced Science · doi:10.1002/advs.202200064 · Cited by 28 · see citing works
Real-time visualization of chromatin modification in isolated nuclei
Sardo, L., Lin, A. M., Khakhina, S., Beckman, L., Ricon, L., Elbezanti, W. O., Jaison, T., Vishwasrao, H. D., Shroff, H., Janetopoulos, C., et al. (2017) · Journal of Cell Science · doi:10.1242/jcs.205823 · Cited by 27 · see citing works
Jarosch, S., Köhlen, J., Sarker, R. S. J., Steiger, K., Janssen, K., Christians, A., Hennig, C., Holler, E., D’Ippolito, E., & Busch, D. H. (2021) · Cell Reports Methods · doi:10.1016/j.crmeth.2021.100104 · Cited by 27 · see citing works
Benchmarking of spatial transcriptomics platforms across six cancer typesPreprint
Cervilla, S., Grases, D., Perez, E., Real, F. X., Musulén, E., Aprea, J., Esteller, M., & Porta‐Pardo, E. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.05.21.593407 · Cited by 26 · see citing works
Scope2Screen: Focus+Context Techniques for Pathology Tumor Assessment in Multivariate Image Data
Jessup, J., Krueger, R., Warchol, S., Hoffer, J., Muhlich, J. L., Ritch, C. C., Gaglia, G., Coy, S., Chen, Y.-A., Lin, J., et al. (2021) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2021.3114786 · Cited by 25 · see citing works
Self-citationVisinity: Visual Spatial Neighborhood Analysis for Multiplexed Tissue Imaging Data
Warchol, S., Krueger, R., Nirmal, A. J., Gaglia, G., Jessup, J., Ritch, C. C., Hoffer, J., Muhlich, J. L., Burger, M. L., Jacks, T., et al. (2022) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2022.3209378 · Cited by 23 · see citing works
Self-citationChan, R., Li, J. J. X., Yeung, W. W., & Chan, A. W. H. (2020) · Diagnostic Cytopathology · doi:10.1002/dc.24344 · Cited by 23 · see citing works
An in vitro tumorigenesis model based on live-cell-generated oxygen and nutrient gradients
Gilmore, A. C., Flaherty, S. J., Somasundaram, V., Scheiblin, D. A., Lockett, S., Wink, D. A., & Heinz, W. F. (2021) · Communications Biology · doi:10.1038/s42003-021-01954-0 · Cited by 22 · see citing works
A PINK1 input threshold arises from positive feedback in the PINK1/Parkin mitophagy decision circuit
Waters, C. S., Angenent, S., Altschuler, S. J., & Wu, L. F. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113260 · Cited by 21 · see citing works
Esselman, A. B., Moser, F. A., Tideman, L. E. M., Migas, L. G., Djambazova, K. V., Colley, M. E., Pingry, E. L., Patterson, N. H., Farrow, M. A., Yang, H., et al. (2024) · Kidney International · doi:10.1016/j.kint.2024.11.008 · Cited by 21 · see citing works
Entropy measures for quantifying complexity in digital pathology and spatial omics
Li, X., Ren, X., & Venugopal, R. (2025) · iScience · doi:10.1016/j.isci.2025.112765 · Cited by 21 · see citing works
A new understanding of tissue biology from MS-based proteomics at single-cell resolution
Nordmann, T. M., Mund, A., & Mann, M. (2024) · Nature Methods · doi:10.1038/s41592-024-02541-x · Cited by 21 · see citing works
Spatial-CITE-seq: spatially resolved high-plex protein and whole transcriptome co-mappingPreprint
Liu, Y., DiStasio, M., Su, G., Asashima, H., Enninful, A., Qin, X., Deng, Y., Bordignon, P., Cassano, M., Tomayko, M. M., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.01.486788 · Cited by 21 · see citing works
Precision cardiovascular medicine: shifting the innovation paradigm
Aikawa, M., Sonawane, A. R., Chelvanambi, S., Asano, T., Halu, A., Matamalas, J. T., Singh, S. A., Uchida, S., Aïkawa, E., Arenas, À., et al. (2025) · Frontiers in Science · doi:10.3389/fsci.2025.1474469 · Cited by 22 · see citing works
Haßdenteufel, S., & Schuldiner, M. (2021) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2021.102102 · Cited by 20 · see citing works
Hunter, B., Nicorescu, I., Foster, E., McDonald, D., Hulme, G., Fuller, A., Thomson, A., Goldsborough, T., Hilkens, C. M. U., Majo, J., et al. (2023) · Cytometry Part A · doi:10.1002/cyto.a.24803 · Cited by 20 · see citing works
Mi, H., Varadhan, R., Cimino‐Mathews, A., Emens, L. A., Santa-Maria, C. A., & Popel, A. S. (2024) · Modern Pathology · doi:10.1016/j.modpat.2024.100652 · Cited by 19 · see citing works
Semi-automated approaches for interrogating spatial heterogeneity of tissue samples
Navikas, V., Kowal, J., Rodriguez, D., Rivest, F., Brajkovic, S., Cassano, M., & Dupouy, D. (2024) · Scientific Reports · doi:10.1038/s41598-024-55387-w · Cited by 19 · see citing works
Zane, L. K., Chapus, F., Pegoraro, G., & Misteli, T. (2017) · Molecular Biology of the Cell · doi:10.1091/mbc.e16-12-0870 · Cited by 19 · see citing works
Tatin, X., Muggiolu, G., Sauvaigo, S., & Breton, J. (2021) · Mutation Research/Reviews in Mutation Research · doi:10.1016/j.mrrev.2021.108388 · Cited by 19 · see citing works
A technical comparison of spatial transcriptomics platforms across six cancer types
Cervilla, S., Mendoza, D. G., Perez, E., Real, F. X., Musulén, E., Aprea, J., Esteller, M., & Porta‐Pardo, E. (2026) · Genome biology · doi:10.1186/s13059-026-03937-y · Cited by 47 · see citing works
Serial multiomics uncovers anti-glioblastoma responses not evident by routine clinical analyses
Ling, A. L., Gantchev, J. K., Prabhu, M. C., Basu, S., Ahn, R., D’Souza, A. D., Masud, N., Ball, A., Nikas, O., Villa, G. R., et al. (2025) · Science Translational Medicine · doi:10.1126/scitranslmed.adv2881 · Cited by 17 · see citing works
Sritharan, D., Wang, S., & Hormoz, S. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2100473118 · Cited by 17 · see citing works
Polyphony: an Interactive Transfer Learning Framework for Single-Cell Data Analysis
Cheng, F., Keller, M. S., Qu, H., Gehlenborg, N., & Wang, Q. (2022) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2022.3209408 · Cited by 17 · see citing works
Application of spatial-omics to the classification of kidney biopsy samples in transplantation
Tasca, P., van den Berg, B. M., Rabelink, T. J., Wang, G., Heijs, B., van Kooten, C., de Vries, A. P. J., & Kers, J. (2024) · Nature Reviews Nephrology · doi:10.1038/s41581-024-00861-x · Cited by 17 · see citing works
Squidpy: a scalable framework for spatial single cell analysis
Palla, G., Spitzer, H., Theis, F., Schaar, A. C., Rybakov, S., Klein, M., Kuemmerle, L. B., Fischer, D. S., Ibarra, I. L., Lotfollahi, M., et al. (2021) · Figshare · doi:10.6084/m9.figshare.c.5273297 · Cited by 17 · see citing works
High-efficiency pharmacogenetic ablation of oligodendrocyte progenitor cells in the adult mouse CNS
Xing, Y. L., Poh, J., Chuang, B. H. A., Moradi, K., Mitew, S., Richardson, W. D., Kilpatrick, T. J., Osanai, Y., & Merson, T. D. (2023) · Cell Reports Methods · doi:10.1016/j.crmeth.2023.100414 · Cited by 16 · see citing works
Flexible Cyclic Immunofluorescence (cyCIF) Using Oligonucleotide Barcoded Antibodies
McMahon, N. P., Jones, J. A., Anderson, A. N., Dietz, M. S., Wong, M. H., & Gibbs, S. L. (2023) · Cancers · doi:10.3390/cancers15030827 · Cited by 15 · see citing works
Computational Methods for Single-Cell Proteomics
Guldberg, S. M., Okholm, T. L. H., McCarthy, E. E., & Spitzer, M. H. (2023) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-020422-050255 · Cited by 16 · see citing works
Cougnoux, A., Mahmoud, L., Johnsson, P. A., Eroğlu, A., Gsell, L., Rosenbauer, J., Sandberg, R., & Hausser, J. (2025) · Scientific Reports · doi:10.1038/s41598-024-83989-x · Cited by 15 · see citing works
Continuous sensing of nutrients and growth factors by the mTORC1-TFEB axis
Sparta, B., Kosaisawe, N., Pargett, M., Patankar, M., DeCuzzi, N. L., & Albeck, J. G. (2023) · eLife · doi:10.7554/elife.74903 · Cited by 14 · see citing works
Advances in tissue-based imaging: impact on oncology research and clinical practice
Rahman, A., Jahangir, C. A., Lynch, S. M., Al-Attar, N., Aura, C. M., Russell, N. M., Lanigan, F. T., & Gallagher, W. M. (2020) · Expert Review of Molecular Diagnostics · doi:10.1080/14737159.2020.1770599 · Cited by 14 · see citing works
Miles, G. J., Powley, I. R., Mohammed, S. B., Howells, L. M., Pringle, J. H., Hammonds, T. R., MacFarlane, M., & Pritchard, C. A. (2020) · Laboratory Investigation · doi:10.1038/s41374-020-00511-3 · Cited by 14 · see citing works
Tyramide-conjugated DNA barcodes enable signal amplification for multiparametric CODEX imaging
Simonson, P. D., Valencia, I., & Patel, S. S. (2022) · Communications Biology · doi:10.1038/s42003-022-03558-8 · Cited by 14 · see citing works
Network inference from perturbation time course data
Sarmah, D., Smith, G. R., Bouhaddou, M., Stern, A. D., Erskine, J., & Birtwistle, M. R. (2022) · npj Systems Biology and Applications · doi:10.1038/s41540-022-00253-6 · Cited by 14 · see citing works
Schrom, E. C., McCaffrey, E., Sreejithkumar, V., Radtke, A. J., Ichise, H., Arroyo-Mejías, A., Speranza, E. E., Arakkal, L., Thakur, N., Grant, S. M., et al. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2412146122 · Cited by 15 · see citing works
Systems immunology spanning tumors, lymph nodes, and periphery
Sidiropoulos, D. N., Ho, W. J., Jaffee, E. M., Kagohara, L. T., & Fertig, E. J. (2023) · Cell Reports Methods · doi:10.1016/j.crmeth.2023.100670 · Cited by 11 · see citing works
Guerriero, J. L., Lin, J., Pastorello, R., Du, Z., Chen, Y.-A., Townsend, M. G., Shimada, K., Hughes, M. E., Ren, S., Tayob, N., et al. (2024) · npj Breast Cancer · doi:10.1038/s41523-023-00605-3 · Cited by 12 · see citing works
Self-citationCadavid, J. L., Li, N. T., & McGuigan, A. P. (2024) · Biophysics Reviews · doi:10.1063/5.0179125 · Cited by 11 · see citing works
Discovery and generalization of tissue structures from spatial omics data
Wu, Z., Kondo, A., McGrady, M., Baker, E. A. G., Chidester, B., Wu, E., Rahim, M. K., Bracey, N. A., Charu, V., Cho, R. J., et al. (2024) · Cell Reports Methods · doi:10.1016/j.crmeth.2024.100838 · Cited by 13 · see citing works
Hunt, G. J., Dane, M. A., Korkola, J. E., Heiser, L. M., & Gagnon-Bartsch, J. A. (2020) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2020.1741379 · Cited by 12 · see citing works
Effects of Sex and 17 β-Estradiol on Cardiac Fibroblast Morphology and Signaling Activities In Vitro
Watts, K. M., & Richardson, W. J. (2021) · Cells · doi:10.3390/cells10102564 · Cited by 12 · see citing works
Sundaram, S., Kim, E. N., Jones, G. M., Sivagnanam, S., Tripathi, M., Miremadi, A., di Pietro, M., Coussens, L. M., Fitzgerald, R. C., Chang, Y. H., et al. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.874255 · Cited by 12 · see citing works
Bady, E., Möller, K., Mandelkow, T., Raedler, J. B., Yang, C. H., Ebner, J., Lurati, M. C. J., Simon, R., Vettorazzi, E., Büscheck, F., et al. (2023) · Molecular Cancer Research · doi:10.1158/1541-7786.mcr-22-0593 · Cited by 12 · see citing works
Guedes, J., Woldmar, N., Szasz, A. M., Wieslander, E., Pawłowski, K., Horvatovich, P., Malm, J., Szadai, L., Németh, I. B., Marko-Varga, G., et al. (2025) · Journal of Proteomics · doi:10.1016/j.jprot.2025.105493 · Cited by 11 · see citing works
Multiplexed immunohistochemistry image analysis using sparse coding
Chang, Y. H., Tsujikawa, T., Margolin, A., Coussens, L. M., & Gray, J. W. (2017) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2017.8037744 · Cited by 11 · see citing works
Ternes, L., Dane, M. A., Gross, S. M., Labrie, M., Mills, G. B., Gray, J. W., Heiser, L. M., & Chang, Y. H. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.22.441005 · Cited by 11 · see citing works
Allais, B. S., Fay, C. J., Kim, D. Y., Semenov, Y. R., & LeBoeuf, N. R. (2023) · Immunological Reviews · doi:10.1111/imr.13257 · Cited by 11 · see citing works
Whalen, R. M., Anderson, A. N., Jones, J. A., Sims, Z., Chang, Y. H., Nederlof, M. A., Wong, M. H., & Gibbs, S. L. (2024) · Scientific Reports · doi:10.1038/s41598-024-57381-8 · Cited by 10 · see citing works
Single-Cell Informatics for Tumor Microenvironment and Immunotherapy
Tian, J., Bai, X., & Quek, C. Y. J. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25084485 · Cited by 11 · see citing works
Zheng, J., Wu, Y.-C., Phillips, E. H., Cai, X., Wang, X., & Lee, S. Y. (2024) · Laboratory Investigation · doi:10.1016/j.labinv.2024.102072 · Cited by 10 · see citing works
Omar, M., Fanelli, G. N., Socciarelli, F., Ullanat, V., Puchala, S. R., Wen, J., Chowdhury, A., Valencia, I., Scatena, C., Marchionni, L., et al. (2025) · Laboratory Investigation · doi:10.1016/j.labinv.2025.104220 · Cited by 10 · see citing works
2D and 3D Multiplexed Subcellular Profiling of Nuclear Instability in Human CancerPreprint
Coy, S., Cheng, B., Lee, J. S., Rashid, R., Browning, L., Xu, Y., Chakrabarty, S. S., Yapp, C., Chan, S. J., Tefft, J. B., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.11.07.566063 · Cited by 10 · see citing works
Self-citationMi, H., Varadhan, R., Cimino‐Mathews, A., Emens, L. A., Santa-Maria, C. A., & Popel, A. S. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.18.572234 · Cited by 10 · see citing works
- Authors
- Lin, J., Fallahi‐Sichani, M., Chen, J., & Sorger, P. K.
- Affiliations
- Harvard University (US)
- Venue
- Current Protocols in Chemical Biology
- Publisher
- Wiley
- Published
- 2016-12
- Volume
- 8
- Issue
- 4
- Pages
- 251-264
- ISSN
- 2160-4762 (ISSN-L)
- PMC
- PMC5233430
- OpenAlex
- W2561429117
- Cited by
- 208
- References
- 20
- Citations by year
- 2026: 24 · 2025: 30 · 2024: 28 · 2023: 34 · 2022: 28 · 2021: 25 · 2020: 17 · 2019: 11 · 2018: 6 · 2017: 5
- FWCI
- 4.59
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Current Protocols in Chemical Biology (publishedVersion, public-domain)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute (U54HL127365)
- National Cancer Institute (K99CA194163)
- National Institute of General Medical Sciences (P50GM107618)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Advanced Fluorescence Microscopy Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- cyclic immunofluorescence, multiplex immunofluorescence, single-cell imaging, epifluorescence microscopy, hydrogen peroxide, signal-to-noise ratio, live-cell imaging, genetically encoded fluorescent proteins
- MeSH terms
- Antibodies, Coloring Agents, Humans, Microscopy, Fluorescence, Immunoconjugates, Cell Line, Tumor, Single-Cell Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
