Brian Skaug
Impact in
- Immunology top 2%
- interferon and immune responses
- Immune Response and Inflammation
- Cancer Research top 5%
- NF-κB Signaling Pathways
Papers in
- Immunology 11
- interferon and immune responses 6
-
- Systemic Sclerosis and Related Diseases 9
- Co-authors
- Zhijian J. ChenFajian HouLijun SunQiu‐Xing JiangHui ZhengXiaomo JiangShervin AssassiMing Xu
- Journals
- Cell (3 papers)Annals of the Rheumatic Diseases (2 papers)Molecular Cell (2 papers)The Journal of Immunology (2 papers)Lara D. Veeken (1 paper)
- Partner nations
- United StatesChinaItaly
In The Last Decade
Brian Skaug
22 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 91
- Immunology 1.4k
- Cancer Research 525
- Molecular Biology 1.4k
- Cell Biology 175
- Oncology 292
Countries citing papers authored by Brian Skaug
This map shows the geographic impact of Brian Skaug'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 Brian Skaug with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Skaug more than expected).
Fields of papers citing papers by Brian Skaug
This network shows the impact of papers produced by Brian Skaug. 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 Brian Skaug. The network helps show where Brian Skaug may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Brian Skaug, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 24 | |
| 2 | 2023 | 5 | |
| 3 | 2022 | 13 | |
| 4 | 2022 | 3 | |
| 5 | 2022 | 2 | |
| 6 | 2021 | 15 | |
| 7 | 2019 | 22 | |
| 8 | 2019 | 67 | |
| 9 | 2019 | 71 | |
| 10 | Antinuclear antibodies in the general population: positive association with inflammatory and vascular biomarkers but not traditional cardiovascular risk factors. | 2019 | 13 |
| 11 | 2018 | 11 | |
| 12 | 2015 | 18 | |
| 13 | 2012 | 9 | |
| 14 | 2011 | 17 | |
| 15 | MAVS Forms Functional Prion-like Aggregates to Activate and Propagate Antiviral Innate Immune Response Hit paper breakdown → | 2011 | 998 |
| 16 | 2011 | 195 | |
| 17 | 2011 | 124 | |
| 18 | 2010 | 175 | |
| 19 | 2009 | 203 | |
| 20 | 2006 | 34 |
About Brian Skaug
Brian Skaug is a scholar working on Immunology, Pathology and Forensic Medicine, Rheumatology, Dermatology and Cancer Research, having authored 22 papers that have together received 2.4k indexed citations. Recurring topics across this work include Systemic Sclerosis and Related Diseases (9 papers), interferon and immune responses (6 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (3 papers), Ubiquitin and proteasome pathways (3 papers), Systemic Lupus Erythematosus Research (3 papers), NF-κB Signaling Pathways (3 papers), RNA regulation and disease (2 papers) and Dermatologic Treatments and Research (2 papers). The work is most often cited by research in Immunology (1.4k citations), Cancer Research (525 citations), Molecular Biology (1.4k citations), Cell Biology (175 citations) and Oncology (292 citations). Brian Skaug has collaborated with scholars based in United States, China and Italy. Frequent co-authors include Zhijian J. Chen, Fajian Hou, Lijun Sun, Qiu‐Xing Jiang, Hui Zheng, Xiaomo Jiang, Shervin Assassi, Ming Xu, Wenwen Zeng and Averil Ma. Their work appears in journals such as Cell, Annals of the Rheumatic Diseases, Molecular Cell, The Journal of Immunology and Lara D. Veeken.
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.