Susan R. Ross

8.8k total citations
142 papers, 6.9k citations indexed

About

Susan R. Ross is a scholar working on Immunology, Genetics and Molecular Biology. According to data from OpenAlex, Susan R. Ross has authored 142 papers receiving a total of 6.9k indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Immunology, 47 papers in Genetics and 45 papers in Molecular Biology. Recurrent topics in Susan R. Ross's work include Virus-based gene therapy research (44 papers), Immunotherapy and Immune Responses (43 papers) and interferon and immune responses (29 papers). Susan R. Ross is often cited by papers focused on Virus-based gene therapy research (44 papers), Immunotherapy and Immune Responses (43 papers) and interferon and immune responses (29 papers). Susan R. Ross collaborates with scholars based in United States, France and United Kingdom. Susan R. Ross's co-authors include Tatyana V. Golovkina, Reed A. Graves, Spyridon Stavrou, John C. Rassa, Jaquelin P. Dudley, Chioma M. Okeoma, Bruce M. Spiegelman, Paul Chrisp, Karen L. Goa and Keith R. Yamamoto and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Susan R. Ross

140 papers receiving 6.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Susan R. Ross United States 51 2.7k 2.4k 1.5k 1.4k 1.0k 142 6.9k
Dirk Lindemann Germany 44 2.2k 0.8× 1.2k 0.5× 1.5k 1.0× 1.7k 1.2× 691 0.7× 131 5.4k
Don J. Diamond United States 49 3.1k 1.2× 2.8k 1.2× 1.2k 0.8× 3.0k 2.2× 1.7k 1.7× 177 9.4k
Lishan Su United States 48 3.4k 1.2× 3.5k 1.5× 594 0.4× 1.9k 1.4× 1.3k 1.2× 184 8.8k
F. Xiao‐Feng Qin China 41 2.6k 0.9× 3.8k 1.6× 727 0.5× 885 0.7× 999 1.0× 115 8.0k
Andrew J. Dorner United States 43 3.1k 1.1× 1.9k 0.8× 885 0.6× 832 0.6× 904 0.9× 87 7.3k
Jürgen Löhler Germany 36 3.4k 1.3× 4.1k 1.7× 2.2k 1.4× 1.1k 0.8× 1.5k 1.4× 99 9.3k
Dhavalkumar D. Patel United States 42 2.3k 0.8× 3.0k 1.3× 1.2k 0.8× 631 0.5× 795 0.8× 67 6.7k
Charles B. Shoemaker United States 47 3.5k 1.3× 1.6k 0.7× 999 0.7× 516 0.4× 745 0.7× 155 9.4k
Mikael Jondal Sweden 55 3.2k 1.2× 6.4k 2.7× 831 0.5× 1.6k 1.2× 2.8k 2.7× 199 12.2k
Daniela Novick Israel 45 3.4k 1.3× 3.9k 1.6× 684 0.5× 1.3k 1.0× 1.4k 1.4× 90 7.9k

Countries citing papers authored by Susan R. Ross

Since Specialization
Citations

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

Fields of papers citing papers by Susan R. Ross

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Susan R. Ross. 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 Susan R. Ross. The network helps show where Susan R. Ross may publish in the future.

Co-authorship network of co-authors of Susan R. Ross

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

All Works

20 of 20 papers shown
1.
Zang, Ruochen, Takahiro Kawagishi, Kruthika Iyer, et al.. (2025). Fatty acid 2-hydroxylase facilitates rotavirus uncoating and endosomal escape. Proceedings of the National Academy of Sciences. 122(36). e2511911122–e2511911122. 1 indexed citations
2.
Ross, Susan R., et al.. (2025). Innate Sensing of Viral Nucleic Acids and Their Use in Antiviral Vaccine Development. Vaccines. 13(2). 193–193. 2 indexed citations
3.
Iyer, Kruthika, et al.. (2024). Entry inhibitors as arenavirus antivirals. Frontiers in Microbiology. 15. 1382953–1382953. 3 indexed citations
4.
Zhao, Wenming, Iván F. Acosta, Francis Alonzo, et al.. (2024). IFI207, a young and fast‐evolving protein, controls retroviral replication via the STING pathway. mBio. 15(7). e0120924–e0120924. 2 indexed citations
5.
Ross, Susan R., et al.. (2024). Data-driven governance and the private sector in mixed health systems. BMJ Global Health. 8(Suppl 5). e014705–e014705.
6.
Lattof, Samantha R., et al.. (2023). Engaging the private sector to deliver quality maternal and newborn health services for universal health coverage: lessons from policy dialogues. BMJ Global Health. 8(Suppl 5). e008939–e008939. 5 indexed citations
7.
Liu, Weisi, Francesca Khani, LaMont Barlow, et al.. (2022). The Cytidine Deaminase APOBEC3G Contributes to Cancer Mutagenesis and Clonal Evolution in Bladder Cancer. Cancer Research. 83(4). 506–520. 20 indexed citations
8.
Ross, Susan R., et al.. (2021). Repair of APOBEC3G-Mutated Retroviral DNA In Vivo Is Facilitated by the Host Enzyme Uracil DNA Glycosylase 2. Journal of Virology. 95(22). e0124421–e0124421. 4 indexed citations
9.
Sarute, Nicolás, et al.. (2021). Signal-regulatory protein alpha is an anti-viral entry factor targeting viruses using endocytic pathways. PLoS Pathogens. 17(6). e1009662–e1009662. 13 indexed citations
10.
Sarute, Nicolás & Susan R. Ross. (2020). CACNA1S haploinsufficiency confers resistance to New World arenavirus infection. Proceedings of the National Academy of Sciences. 117(32). 19497–19506. 12 indexed citations
11.
Li, Jian J., et al.. (2020). A recessive Trim2 mutation causes an axonal neuropathy in mice. Neurobiology of Disease. 140. 104845–104845. 10 indexed citations
12.
Tokuyama, Maria, et al.. (2019). Human APOBEC3G Prevents Emergence of Infectious Endogenous Retrovirus in Mice. Journal of Virology. 93(20). 14 indexed citations
13.
14.
15.
Lee, James, David C. Kim, Michael S. Gee, et al.. (2002). Interleukin-12 inhibits angiogenesis and growth of transplanted but not in situ mouse mammary tumor virus-induced mammary carcinomas.. PubMed. 62(3). 747–55. 28 indexed citations
16.
Latinkic, Branko, Fan‐E Mo, Neal G. Copeland, et al.. (2001). Promoter Function of the Angiogenic Inducer Cyr61Gene in Transgenic Mice: Tissue Specificity, Inducibility During Wound Healing, and Role of the Serum Response Element*. Endocrinology. 142(6). 2549–2557. 54 indexed citations
17.
Valet, Philippe, Danica Grujić, Jennifer M. Wade, et al.. (2000). Expression of Human α2-Adrenergic Receptors in Adipose Tissue of β3-Adrenergic Receptor-deficient Mice Promotes Diet-induced Obesity. Journal of Biological Chemistry. 275(44). 34797–34802. 80 indexed citations
18.
Soloveva, Veronica, et al.. (1997). Transgenic Mice Overexpressing the β1-Adrenergic Receptor in Adipose Tissue Are Resistant to Obesity. Molecular Endocrinology. 11(1). 27–38. 91 indexed citations
19.
Cofer, Shelagh A. & Susan R. Ross. (1996). The murine gene encoding apolipoprotein D exhibits a unique expression pattern as compared to other species. Gene. 171(2). 261–263. 16 indexed citations
20.
Ross, Susan R., et al.. (1990). Negative Regulation in Correct Tissue-Specific Expression of Mouse Mammary Tumor Virus in Transgenic Mice. Molecular and Cellular Biology. 10(11). 5822–5829. 28 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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