Mario Pujato

1.1k total citations
20 papers, 594 citations indexed

About

Mario Pujato is a scholar working on Molecular Biology, Immunology and Hematology. According to data from OpenAlex, Mario Pujato has authored 20 papers receiving a total of 594 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 9 papers in Immunology and 4 papers in Hematology. Recurrent topics in Mario Pujato's work include Acute Myeloid Leukemia Research (4 papers), interferon and immune responses (3 papers) and Dermatology and Skin Diseases (3 papers). Mario Pujato is often cited by papers focused on Acute Myeloid Leukemia Research (4 papers), interferon and immune responses (3 papers) and Dermatology and Skin Diseases (3 papers). Mario Pujato collaborates with scholars based in United States, Japan and Netherlands. Mario Pujato's co-authors include András Fiser, Matthew T. Weirauch, Leah C. Kottyan, Daniel Miller, Xiaoting Chen, Carmy Forney, Kenneth M. Kaufman, Albert Frank Magnusen, Artem Barski and John B. Harley and has published in prestigious journals such as Nature, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Mario Pujato

20 papers receiving 589 citations

Peers

Mario Pujato

IMMUN

ONCOL

RHEUM

GENET

Janet Schaefer-Klein United States

Nicolás Fissolo Spain

Masashi Yukawa Japan

Evelyn Lau United Kingdom

André Luíz Teles e Silva Brazil

Vyacheslav A. Adarichev United States

Claudia Haftmann Germany

Anagha Divekar United States

Eduardo Cuende Spain

Véronique Adoue France

Janet Schaefer-Klein United States

Mario Pujato

299 ×1.2

215 ×1.4

IMMUN

87 ×0.8

ONCOL

79 ×0.8

RHEUM

97 ×1.1

GENET

Citations per year, relative to Mario Pujato Mario Pujato (= 1×) peers Janet Schaefer-Klein

Countries citing papers authored by Mario Pujato

Since Specialization

Citations

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

Fields of papers citing papers by Mario Pujato

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mario Pujato. 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 Mario Pujato. The network helps show where Mario Pujato may publish in the future.

Co-authorship network of co-authors of Mario Pujato

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

All Works

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20 of 20 papers shown

Yang, Jun‐Qi, Chen Wang, Ramesh C. Nayak, et al.. (2025). Genetic and epigenetic regulation of Treg cell fitness by autism-related chromatin remodeler CHD8. Cellular & Molecular Biology Letters. 30(1). 36–36. 1 indexed citations

Barreyro, Laura, Kathleen Hueneman, Michael A. Wyder, et al.. (2024). Dysregulated innate immune signaling cooperates with RUNX1 mutations to transform an MDS-like disease to AML. iScience. 27(6). 109809–109809. 7 indexed citations

Dexheimer, Phillip J., Mario Pujato, Krishna M. Roskin, & Matthew T. Weirauch. (2023). VExD: a curated resource for human gene expression alterations following viral infection. G3 Genes Genomes Genetics. 13(10). 1 indexed citations

Bartholdy, Boris, Kith Pradhan, Tushar D. Bhagat, et al.. (2022). PU.1-Dependent Enhancer Inhibition Separates Tet2 -Deficient Hematopoiesis from Malignant Transformation. Blood Cancer Discovery. 3(5). 444–467. 11 indexed citations

Williams, James, Rashika Joshi, David Haslam, et al.. (2022). Multi-omic characterization of pediatric ARDS via nasal brushings. Respiratory Research. 23(1). 181–181. 2 indexed citations

Parameswaran, Sreeja, Carmy Forney, Lee Edsall, et al.. (2022). Epigenetic and transcriptional dysregulation in CD4+ T cells in patients with atopic dermatitis. PLoS Genetics. 18(5). e1009973–e1009973. 10 indexed citations

Kottyan, Leah C., Sreeja Parameswaran, Carmy Forney, et al.. (2022). Epigenetic and Transcriptional Dysregulation in T cells of Patients with Atopic Dermatitis. Journal of Allergy and Clinical Immunology. 149(2). AB5–AB5. 1 indexed citations

Hass, Matthew R., Sreeja Parameswaran, Mario Pujato, et al.. (2021). Runx1 shapes the chromatin landscape via a cascade of direct and indirect targets. PLoS Genetics. 17(6). e1009574–e1009574. 15 indexed citations

Lu, Xiaoming, Xiaoting Chen, Carmy Forney, et al.. (2021). Global discovery of lupus genetic risk variant allelic enhancer activity. Nature Communications. 12(1). 1611–1611. 40 indexed citations

10.

Hueneman, Kathleen, Kwangmin Choi, Melinda E. Varney, et al.. (2020). TIFAB Regulates USP15-Mediated p53 Signaling during Stressed and Malignant Hematopoiesis. Cell Reports. 30(8). 2776–2790.e6. 28 indexed citations

11.

Hammonds, J., et al.. (2020). Comparative analysis of human microglial models for studies of HIV replication and pathogenesis. Retrovirology. 17(1). 35–35. 46 indexed citations

12.

Parameswaran, Sreeja, Carmy Forney, Daniel Miller, et al.. (2019). NFκB transcription factor binding is altered at many Atopic Dermatitis disease loci. Journal of Allergy and Clinical Immunology. 143(2). AB65–AB65. 2 indexed citations

13.

Rao, Vasudev R, Xuhong Wu, Santhamani Ramasamy, et al.. (2019). CCL2 mobilizes ALIX to facilitate Gag-p6 mediated HIV-1 virion release. eLife. 8. 13 indexed citations

14.

Harley, John B., Xiaoting Chen, Mario Pujato, et al.. (2018). Transcription factors operate across disease loci, with EBNA2 implicated in autoimmunity. Nature Genetics. 50(5). 699–707. 241 indexed citations

15.

Cao, Longyue L., Dario F. Riascos‐Bernal, Prameladevi Chinnasamy, et al.. (2016). Control of mitochondrial function and cell growth by the atypical cadherin Fat1. Nature. 539(7630). 575–578. 51 indexed citations

16.

Pujato, Mario, et al.. (2016). Iterative sorting of apical and basolateral cargo in Madin–Darby canine kidney cells. Molecular Biology of the Cell. 27(14). 2259–2271. 7 indexed citations

17.

Barreyro, Laura, Lyndsey Bolanos, Mario Pujato, et al.. (2016). Inhibition of UBE2N As a Therapeutic Approach in Myelodysplastic Syndromes (MDS) and Acute Myeloid Leukemia (AML). Blood. 128(22). 579–579. 2 indexed citations

18.

Pujato, Mario, et al.. (2014). Prediction of DNA binding motifs from 3D models of transcription factors; identifying TLX3 regulated genes. Nucleic Acids Research. 42(22). 13500–13512. 68 indexed citations

19.

Pujato, Mario, Thomas MacCarthy, András Fiser, & Aviv Bergman. (2013). The Underlying Molecular and Network Level Mechanisms in the Evolution of Robustness in Gene Regulatory Networks. PLoS Computational Biology. 9(1). e1002865–e1002865. 15 indexed citations

20.

Jesus, Magdia De, Antonio Nakouzi, Radamés J. B. Cordero, et al.. (2009). Identification of Linear Epitopes in Bacillus anthracis Protective Antigen Bound by Neutralizing Antibodies. Journal of Biological Chemistry. 284(37). 25077–25086. 33 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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