Priscila Muñoz Sandoval

979 total citations
7 papers, 613 citations indexed

About

Priscila Muñoz Sandoval is a scholar working on Immunology, Oncology and Infectious Diseases. According to data from OpenAlex, Priscila Muñoz Sandoval has authored 7 papers receiving a total of 613 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Immunology, 3 papers in Oncology and 1 paper in Infectious Diseases. Recurrent topics in Priscila Muñoz Sandoval's work include T-cell and B-cell Immunology (3 papers), Cancer Immunotherapy and Biomarkers (3 papers) and Immunotherapy and Immune Responses (3 papers). Priscila Muñoz Sandoval is often cited by papers focused on T-cell and B-cell Immunology (3 papers), Cancer Immunotherapy and Biomarkers (3 papers) and Immunotherapy and Immune Responses (3 papers). Priscila Muñoz Sandoval collaborates with scholars based in United States, France and Austria. Priscila Muñoz Sandoval's co-authors include Michael D. Rosenblum, Mariela Pauli, Kimberly Loo, Alain P. Algazi, Michael Alvarado, Adil Daud, Keyon Taravati, Katy K. Tsai, Matthew F. Krummel and Adi Nosrati and has published in prestigious journals such as Journal of Clinical Investigation, Journal of Clinical Oncology and Annals of the New York Academy of Sciences.

In The Last Decade

Priscila Muñoz Sandoval

7 papers receiving 608 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Priscila Muñoz Sandoval United States 6 394 391 98 79 50 7 613
Keyon Taravati United States 8 451 1.1× 406 1.0× 117 1.2× 61 0.8× 66 1.3× 8 671
Amelia Roman Aguilera Australia 9 488 1.2× 366 0.9× 103 1.1× 53 0.7× 13 0.3× 9 642
Kathleen P. Lowler United States 15 684 1.7× 227 0.6× 114 1.2× 73 0.9× 22 0.4× 20 1.0k
Akihito Fujimi Japan 9 152 0.4× 275 0.7× 213 2.2× 39 0.5× 45 0.9× 41 739
Solène Perez France 5 700 1.8× 715 1.8× 107 1.1× 107 1.4× 15 0.3× 7 966
Katarzyna Trebska-McGowan United States 6 480 1.2× 596 1.5× 171 1.7× 55 0.7× 18 0.4× 7 777
Jessica Esandrio United States 7 270 0.7× 503 1.3× 171 1.7× 69 0.9× 57 1.1× 10 640
Morganna Freeman-Keller United States 4 197 0.5× 620 1.6× 127 1.3× 159 2.0× 24 0.5× 4 699
Nicola Bielefeld Germany 9 137 0.3× 267 0.7× 105 1.1× 104 1.3× 30 0.6× 9 399
Mohamed ElTanbouly United States 11 477 1.2× 296 0.8× 121 1.2× 58 0.7× 12 0.2× 15 675

Countries citing papers authored by Priscila Muñoz Sandoval

Since Specialization
Citations

This map shows the geographic impact of Priscila Muñoz Sandoval'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 Priscila Muñoz Sandoval with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Priscila Muñoz Sandoval more than expected).

Fields of papers citing papers by Priscila Muñoz Sandoval

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Priscila Muñoz Sandoval. 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 Priscila Muñoz Sandoval. The network helps show where Priscila Muñoz Sandoval may publish in the future.

Co-authorship network of co-authors of Priscila Muñoz Sandoval

This figure shows the co-authorship network connecting the top 25 collaborators of Priscila Muñoz Sandoval. A scholar is included among the top collaborators of Priscila Muñoz Sandoval 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 Priscila Muñoz Sandoval. Priscila Muñoz Sandoval is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
1.
Kalekar, Lokesh A., Jarish N. Cohen, Nicolas Prevel, et al.. (2019). Regulatory T cells in skin are uniquely poised to suppress profibrotic immune responses. Science Immunology. 4(39). 96 indexed citations
2.
Remedios, Kelly A., Bahar Zirak, Priscila Muñoz Sandoval, et al.. (2018). The TNFRSF members CD27 and OX40 coordinately limit T H 17 differentiation in regulatory T cells. Science Immunology. 3(30). 36 indexed citations
3.
Loo, Kimberly, Katy K. Tsai, Kelly M. Mahuron, et al.. (2017). Partially exhausted tumor-infiltrating lymphocytes predict response to combination immunotherapy. JCI Insight. 2(14). 56 indexed citations
4.
Cordoro, Kelly M., Keyon Taravati, Priscila Muñoz Sandoval, et al.. (2017). Skin-infiltrating, interleukin-22–producing T cells differentiate pediatric psoriasis from adult psoriasis. Journal of the American Academy of Dermatology. 77(3). 417–424. 38 indexed citations
5.
Loo, Kimberly, Katy K. Tsai, Mariela Pauli, et al.. (2016). Novel T cell exhaustion marker to predict monotherapy PD-1 compared to combination CTLA-4 and PD-1 response in melanoma.. Journal of Clinical Oncology. 34(15_suppl). 9520–9520. 2 indexed citations
6.
Daud, Adil, Kimberly Loo, Mariela Pauli, et al.. (2016). Tumor immune profiling predicts response to anti–PD-1 therapy in human melanoma. Journal of Clinical Investigation. 126(9). 3447–3452. 378 indexed citations
7.
Kwak, Joanne Y.H., et al.. (1994). Biological Basis of Fetoplacental Antigenic Determinants in the Induction of the Antiphospholipid Antibody Syndrome and Recurrent Pregnancy Loss. Annals of the New York Academy of Sciences. 731(1). 242–245. 7 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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