Raphaël Gottardo

41.7k total citations · 5 hit papers
130 papers, 8.7k citations indexed

About

Raphaël Gottardo is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Raphaël Gottardo has authored 130 papers receiving a total of 8.7k indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Molecular Biology, 43 papers in Immunology and 21 papers in Oncology. Recurrent topics in Raphaël Gottardo's work include Single-cell and spatial transcriptomics (41 papers), Gene expression and cancer classification (35 papers) and T-cell and B-cell Immunology (22 papers). Raphaël Gottardo is often cited by papers focused on Single-cell and spatial transcriptomics (41 papers), Gene expression and cancer classification (35 papers) and T-cell and B-cell Immunology (22 papers). Raphaël Gottardo collaborates with scholars based in United States, Canada and Switzerland. Raphaël Gottardo's co-authors include Greg Finak, Andrew McDavid, Ryan R. Brinkman, Kenneth Lo, Martin Prlic, M. Juliana McElrath, Peter S. Linsley, Chloe K. Slichter, Vivian H. Gersuk and Masanao Yajima and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and The Lancet.

In The Last Decade

Raphaël Gottardo

128 papers receiving 8.6k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data

2015 1.6k citations Greg Finak, Andrew McDavid et al. Genome biology profile →
Exosomes in human semen carry a distinctive repertoire of small non-coding RNAs with potential regulatory functions

2014 464 citations Lucia Vojtech, Sean M. Hughes et al. profile →
Spatial transcriptomics at subspot resolution with BayesSpace

2021 448 citations Edward Zhao, Matthew R. Stone et al. Nature Biotechnology profile →
Orchestrating single-cell analysis with Bioconductor

2019 423 citations Robert A. Amezquita, Étienne Becht et al. profile →
Safety and immunogenicity of a mRNA rabies vaccine in healthy adults: an open-label, non-randomised, prospective, first-in-human phase 1 clinical trial

2017 373 citations Greg Finak, Raphaël Gottardo et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Raphaël Gottardo United States	40	5.2k	2.4k	1.4k	962	808	130	8.7k
Evan W. Newell United States	52	4.5k 0.9×	5.5k 2.3×	2.2k 1.6×	708 0.7×	471 0.6×	149	11.2k
Nir Yosef United States	46	7.8k 1.5×	4.5k 1.9×	1.6k 1.1×	1.6k 1.7×	809 1.0×	116	13.4k
Christoph Hafemeister United States	12	8.4k 1.6×	3.9k 1.6×	1.7k 1.2×	1.8k 1.9×	795 1.0×	19	12.7k
Stephen McQuaid United Kingdom	48	3.2k 0.6×	2.0k 0.8×	2.2k 1.6×	1.1k 1.1×	882 1.1×	148	11.3k
Thomas Höfer Germany	60	4.8k 0.9×	3.2k 1.4×	1.5k 1.1×	912 0.9×	720 0.9×	184	10.3k
Greg Finak United States	23	3.2k 0.6×	1.3k 0.6×	1.2k 0.8×	1.1k 1.1×	316 0.4×	42	5.3k
Richard H. Scheuermann United States	44	5.7k 1.1×	1.7k 0.7×	1.2k 0.8×	546 0.6×	1.2k 1.5×	158	9.8k
Alvis Brāzma United Kingdom	50	11.0k 2.1×	1.1k 0.5×	743 0.5×	1.4k 1.4×	1.6k 2.0×	132	14.7k
Niall J. Lennon United States	30	4.4k 0.8×	1.3k 0.6×	604 0.4×	944 1.0×	656 0.8×	66	8.3k
Soumya Raychaudhuri United States	59	7.1k 1.4×	4.5k 1.9×	1.4k 1.0×	1.5k 1.5×	3.1k 3.8×	176	15.1k

Countries citing papers authored by Raphaël Gottardo

Since Specialization

Citations

This map shows the geographic impact of Raphaël Gottardo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Raphaël Gottardo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphaël Gottardo more than expected).

Fields of papers citing papers by Raphaël Gottardo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Raphaël Gottardo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Raphaël Gottardo. The network helps show where Raphaël Gottardo may publish in the future.

Co-authorship network of co-authors of Raphaël Gottardo

This figure shows the co-authorship network connecting the top 25 collaborators of Raphaël Gottardo. A scholar is included among the top collaborators of Raphaël Gottardo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Raphaël Gottardo. Raphaël Gottardo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Su, Yapeng, et al.. (2026). The ubiquitin ligase KLHL6 drives resistance to CD8+ T cell dysfunction. Nature. 651(8105). 451–461. 1 indexed citations

Alencar, Gabriel F., Yapeng Su, Valentin Voillet, et al.. (2025). Triple checkpoint blockade of PD-1, Tim-3, and Lag-3 enhances adoptive T cell immunotherapy in a mouse model of ovarian cancer. Proceedings of the National Academy of Sciences. 122(39). e2419888122–e2419888122.

Fries, Anissa, Fanny Saidoune, François Kuonen, et al.. (2023). Differentiation of IL-26+ TH17 intermediates into IL-17A producers via epithelial crosstalk in psoriasis. Nature Communications. 14(1). 3878–3878. 32 indexed citations

Voillet, Valentin, Trisha R. Berger, Kelly M. McKenna, et al.. (2022). An In Vivo Model of Human Macrophages in Metastatic Melanoma. The Journal of Immunology. 209(3). 606–620. 7 indexed citations

Church, Candice D., Thomas H. Pulliam, Song Y. Park, et al.. (2022). Transcriptional and functional analyses of neoantigen-specific CD4 T cells during a profound response to anti-PD-L1 in metastatic Merkel cell carcinoma. Journal for ImmunoTherapy of Cancer. 10(9). e005328–e005328. 14 indexed citations

Giraldo, Nicolás A., Sneha Berry, Étienne Becht, et al.. (2021). Spatial UMAP and Image Cytometry for Topographic Immuno-oncology Biomarker Discovery. Cancer Immunology Research. 9(11). 1262–1269. 6 indexed citations

Finak, Greg, Leonard D’Amico, Nina Bhardwaj, et al.. (2021). New interpretable machine-learning method for single-cell data reveals correlates of clinical response to cancer immunotherapy. Patterns. 2(12). 100372–100372. 21 indexed citations

Becht, Étienne, Charles‐Antoine Dutertre, Peter A. Morawski, et al.. (2021). High-throughput single-cell quantification of hundreds of proteins using conventional flow cytometry and machine learning. Science Advances. 7(39). eabg0505–eabg0505. 40 indexed citations

Zhao, Edward, Matthew R. Stone, Xing Ren, et al.. (2021). Spatial transcriptomics at subspot resolution with BayesSpace. Nature Biotechnology. 39(11). 1375–1384. 448 indexed citations breakdown →

10.

Sheih, Alyssa, Valentin Voillet, Laïla‐Aïcha Hanafi, et al.. (2020). Clonal kinetics and single-cell transcriptional profiling of CAR-T cells in patients undergoing CD19 CAR-T immunotherapy. Nature Communications. 11(1). 219–219. 177 indexed citations

11.

Anderson, Kristin G., Valentin Voillet, Breanna M. Bates, et al.. (2019). Engineered Adoptive T-cell Therapy Prolongs Survival in a Preclinical Model of Advanced-Stage Ovarian Cancer. Cancer Immunology Research. 7(9). 1412–1425. 27 indexed citations

12.

Fourati, Slim, Susan Pereira Ribeiro, Aarthi Talla, et al.. (2019). Integrated systems approach defines the antiviral pathways conferring protection by the RV144 HIV vaccine. Nature Communications. 10(1). 863–863. 24 indexed citations

13.

Noto, Alessandra, Francesco A. Procopio, Riddhima Banga, et al.. (2018). CD32 ⁺ and PD-1 ⁺ Lymph Node CD4 T Cells Support Persistent HIV-1 Transcription in Treated Aviremic Individuals. Journal of Virology. 92(20). 33 indexed citations

14.

Lu, Daniel, Andrew McDavid, Sarah Kongpachith, et al.. (2018). T Cell–Dependent Affinity Maturation and Innate Immune Pathways Differentially Drive Autoreactive B Cell Responses in Rheumatoid Arthritis. Arthritis & Rheumatology. 70(11). 1732–1744. 72 indexed citations

15.

Shah, Javeed A., Munyaradzi Musvosvi, Muki Shey, et al.. (2017). A Functional Toll-Interacting Protein Variant Is Associated with Bacillus Calmette-Guérin–Specific Immune Responses and Tuberculosis. American Journal of Respiratory and Critical Care Medicine. 196(4). 502–511. 34 indexed citations

16.

Finak, Greg, Andrew McDavid, Masanao Yajima, et al.. (2015). MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data. Genome biology. 16(1). 278–278. 1570 indexed citations breakdown →

17.

Hladik, Florian, Adam Burgener, Lamar Ballweber, et al.. (2015). Mucosal effects of tenofovir 1% gel. eLife. 4. 51 indexed citations

18.

Robertson, A. Gordon, Leping Li, Xuekui Zhang, et al.. (2012). Identification and analysis of murine pancreatic islet enhancers. Diabetologia. 56(3). 542–552. 45 indexed citations

19.

Scott‐Boyer, Marie‐Pier, et al.. (2012). An Integrated Hierarchical Bayesian Model for Multivariate eQTL Mapping. Statistical Applications in Genetics and Molecular Biology. 11(4). 19 indexed citations

20.

Gottardo, Raphaël, Julian Besag, Matthew Stephens, & Alejandro Murua. (2005). Probabilistic segmentation and intensity estimation for microarray images. Biostatistics. 7(1). 85–99. 22 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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