Emily V. Mesev

748 total citations · 1 hit paper
9 papers, 521 citations indexed

About

Emily V. Mesev is a scholar working on Immunology, Oncology and Molecular Biology. According to data from OpenAlex, Emily V. Mesev has authored 9 papers receiving a total of 521 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Immunology, 5 papers in Oncology and 3 papers in Molecular Biology. Recurrent topics in Emily V. Mesev's work include interferon and immune responses (4 papers), Cytokine Signaling Pathways and Interactions (3 papers) and Drug Transport and Resistance Mechanisms (2 papers). Emily V. Mesev is often cited by papers focused on interferon and immune responses (4 papers), Cytokine Signaling Pathways and Interactions (3 papers) and Drug Transport and Resistance Mechanisms (2 papers). Emily V. Mesev collaborates with scholars based in United States and Japan. Emily V. Mesev's co-authors include Alexander Ploß, Robert A. LeDesma, Ronald E. Cannon, David S. Miller, Mark J. Federspiel, Blake A. Jacobson, Yan Ji, Shaogeng Tang, Stephen J. Russell and Manish R. Patel and has published in prestigious journals such as Journal of Clinical Investigation, Journal of Virology and Molecular Pharmacology.

In The Last Decade

Emily V. Mesev

9 papers receiving 511 citations

Hit 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.

Decoding type I and III interferon signalling during viral infection

2019 355 citations Emily V. Mesev, Robert A. LeDesma et al. Nature Microbiology profile →

Peers

Emily V. Mesev

IMMUN

MB

ID

ONCOL

GENET

Ariel Isaacs Australia

Meijie Tian United States

Nicholas L. Baird United States

Andrea Di Pietro Italy

Margaret H. Beddall United States

J. Michael Stolley United States

Spyridon Stavrou United States

Jacob P. van Vloten Canada

Maria L. Mouchess United States

Michael Flora United States

Ariel Isaacs Australia

Emily V. Mesev

325 ×1.5

IMMUN

135 ×0.8

MB

195 ×1.3

ID

133 ×1.0

ONCOL

45 ×0.4

GENET

Citations per year, relative to Emily V. Mesev Emily V. Mesev (= 1×) peers Ariel Isaacs

Countries citing papers authored by Emily V. Mesev

Since Specialization

Citations

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

Fields of papers citing papers by Emily V. Mesev

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emily V. Mesev. 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 Emily V. Mesev. The network helps show where Emily V. Mesev may publish in the future.

Co-authorship network of co-authors of Emily V. Mesev

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

All Works

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9 of 9 papers shown

1.

Gabor, Kristin A., Emily V. Mesev, Jennifer H. Madenspacher, et al.. (2024). Sterol biosynthesis regulates TLR signaling and the innate immune response in a Smith-Lemli-Opitz syndrome model. Journal of Clinical Investigation. 134(6). 4 indexed citations

2.

Lin, Aaron E., Emily V. Mesev, Jared E. Toettcher, & Alexander Ploß. (2024). Engineered chimeric receptors for dissecting interferon signaling. Journal of Virology. 98(10). e0168023–e0168023. 1 indexed citations

3.

Yang, Xiaoyu, et al.. (2023). pYtags enable spatiotemporal measurements of receptor tyrosine kinase signaling in living cells. eLife. 12. 8 indexed citations

4.

Mesev, Emily V., et al.. (2023). Synthetic Heterodimers of Type III Interferon Receptors Require TYK2 for STAT Activation. Journal of Interferon & Cytokine Research. 43(9). 414–426. 5 indexed citations

5.

Mesev, Emily V., Aaron E. Lin, Brigitte Heller, et al.. (2023). Membrane-proximal motifs encode differences in signaling strength between type I and III interferon receptors. Science Signaling. 16(806). eadf5494–eadf5494. 5 indexed citations

6.

Mesev, Emily V., Robert A. LeDesma, & Alexander Ploß. (2019). Decoding type I and III interferon signalling during viral infection. Nature Microbiology. 4(6). 914–924. 355 indexed citations breakdown →

7.

Mesev, Emily V., David S. Miller, & Ronald E. Cannon. (2017). Ceramide 1-Phosphate Increases P-Glycoprotein Transport Activity at the Blood-Brain Barrier via Prostaglandin E2 Signaling. Molecular Pharmacology. 91(4). 373–382. 24 indexed citations

8.

Evans, Rebecca A., et al.. (2016). Selective induction of P-glycoprotein at the CNS barriers during symptomatic stage of an ALS animal model. Neuroscience Letters. 639. 103–113. 33 indexed citations

9.

Patel, Manish R., Blake A. Jacobson, Yan Ji, et al.. (2015). Vesicular stomatitis virus expressing interferon-β is oncolytic and promotes antitumor immune responses in a syngeneic murine model of non-small cell lung cancer. Oncotarget. 6(32). 33165–33177. 86 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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