Brian C. Schaefer

5.3k total citations
64 papers, 4.2k citations indexed

About

Brian C. Schaefer is a scholar working on Immunology, Cancer Research and Molecular Biology. According to data from OpenAlex, Brian C. Schaefer has authored 64 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Immunology, 18 papers in Cancer Research and 13 papers in Molecular Biology. Recurrent topics in Brian C. Schaefer's work include Immune Cell Function and Interaction (18 papers), T-cell and B-cell Immunology (17 papers) and NF-κB Signaling Pathways (16 papers). Brian C. Schaefer is often cited by papers focused on Immune Cell Function and Interaction (18 papers), T-cell and B-cell Immunology (17 papers) and NF-κB Signaling Pathways (16 papers). Brian C. Schaefer collaborates with scholars based in United States, Australia and South Africa. Brian C. Schaefer's co-authors include Philippa Marrack, John W. Kappler, Ross M. Kedl, David A. Hildeman, Samuel H. Speck, Tom Mitchell, Suman Paul, Jack L. Strominger, William A. Rees and Michele L. Schaefer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of Experimental Medicine.

In The Last Decade

Brian C. Schaefer

63 papers receiving 4.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian C. Schaefer United States 33 2.2k 1.4k 977 618 610 64 4.2k
Marc J. Servant Canada 31 2.3k 1.0× 1.5k 1.0× 859 0.9× 597 1.0× 817 1.3× 54 4.0k
Yaël Mamane Canada 21 1.7k 0.7× 1.7k 1.2× 939 1.0× 496 0.8× 502 0.8× 27 3.5k
Klaus‐Peter Knobeloch Germany 39 2.6k 1.2× 2.5k 1.8× 1.0k 1.0× 395 0.6× 630 1.0× 78 5.3k
Toufic Renno France 30 2.2k 1.0× 1.2k 0.9× 563 0.6× 335 0.5× 467 0.8× 55 3.7k
Craig M. Walsh United States 34 2.1k 0.9× 1.9k 1.4× 564 0.6× 329 0.5× 682 1.1× 77 4.1k
Massimiliano Pagani Italy 32 1.5k 0.7× 2.0k 1.4× 551 0.6× 896 1.4× 695 1.1× 62 4.2k
Chang‐Sung Koh Japan 21 2.9k 1.3× 1.3k 0.9× 424 0.4× 337 0.5× 787 1.3× 65 4.1k
Jian‐Xin Lin United States 25 3.4k 1.5× 1.2k 0.9× 2.1k 2.1× 500 0.8× 355 0.6× 42 5.2k
Jun–ichi Fujisawa Japan 40 3.0k 1.3× 3.0k 2.2× 1.1k 1.1× 509 0.8× 545 0.9× 101 6.5k
Beichu Guo United States 22 2.4k 1.1× 1.2k 0.8× 639 0.7× 685 1.1× 381 0.6× 28 3.4k

Countries citing papers authored by Brian C. Schaefer

Since Specialization
Citations

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

Fields of papers citing papers by Brian C. Schaefer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian C. Schaefer. 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 C. Schaefer. The network helps show where Brian C. Schaefer may publish in the future.

Co-authorship network of co-authors of Brian C. Schaefer

This figure shows the co-authorship network connecting the top 25 collaborators of Brian C. Schaefer. A scholar is included among the top collaborators of Brian C. Schaefer 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 Brian C. Schaefer. Brian C. Schaefer 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.
Rader, Madeline, Lianying Yan, Bronwyn M. Gunn, et al.. (2025). A recombinant Cedar virus preclinical model that recapitulates neurological features of henipavirus disease. iScience. 28(10). 113571–113571. 1 indexed citations
2.
Ruchinskas, Allison, et al.. (2024). A20 intrinsically influences human effector T‐cell survival and function by regulating both NF‐κB and JNK signaling. European Journal of Immunology. 54(12). e2451245–e2451245.
3.
Laing, Eric D., et al.. (2022). Longitudinal Tracing of Lyssavirus Infection in Mice via In Vivo Bioluminescence Imaging. Methods in molecular biology. 2524. 369–394. 1 indexed citations
4.
Shroff, Hari, et al.. (2021). Signaling through polymerization and degradation: Analysis and simulations of T cell activation mediated by Bcl10. PLoS Computational Biology. 17(5). e1007986–e1007986. 3 indexed citations
5.
6.
Drummond, Rebecca A., Muthulekha Swamydas, Vasileios Oikonomou, et al.. (2019). CARD9+ microglia promote antifungal immunity via IL-1β- and CXCL1-mediated neutrophil recruitment. Nature Immunology. 20(5). 559–570. 171 indexed citations
7.
8.
Zhi, Huijun, Batsukh Dorjbal, Subha Philip, et al.. (2015). HTLV-1 Tax Stimulates Ubiquitin E3 Ligase, Ring Finger Protein 8, to Assemble Lysine 63-Linked Polyubiquitin Chains for TAK1 and IKK Activation. PLoS Pathogens. 11(8). e1005102–e1005102. 41 indexed citations
9.
Latoche, Joseph R., et al.. (2012). Controlled Cortical Impact and Craniotomy Induce Strikingly Similar Profiles of Inflammatory Gene Expression, but with Distinct Kinetics. Frontiers in Neurology. 3. 155–155. 83 indexed citations
10.
Paul, Suman & Brian C. Schaefer. (2012). Selective autophagy regulates T cell activation. Autophagy. 8(11). 1690–1692. 14 indexed citations
11.
Paul, Suman, Anuj Kashyap, Wei Jia, You‐Wen He, & Brian C. Schaefer. (2012). Selective Autophagy of the Adaptor Protein Bcl10 Modulates T Cell Receptor Activation of NF-κB. Immunity. 36(6). 947–958. 166 indexed citations
12.
Lamb, Erika, John Pesce, Diana K. Riner, et al.. (2010). Blood Fluke Exploitation of Non-Cognate CD4+ T Cell Help to Facilitate Parasite Development. PLoS Pathogens. 6(4). e1000892–e1000892. 30 indexed citations
13.
Rossman, Jeremy S., et al.. (2008). Multiple Protein Domains Mediate Interaction between Bcl10 and MALT1. Journal of Biological Chemistry. 283(47). 32419–32431. 33 indexed citations
14.
Rossman, Jeremy S., et al.. (2006). POLKADOTS Are Foci of Functional Interactions in T-Cell Receptor–mediated Signaling to NF-κB. Molecular Biology of the Cell. 17(5). 2166–2176. 35 indexed citations
15.
Zhu, Yanan, Bradley Jay Swanson, Michael Wang, et al.. (2004). Constitutive association of the proapoptotic protein Bim with Bcl-2-related proteins on mitochondria in T cells. Proceedings of the National Academy of Sciences. 101(20). 7681–7686. 104 indexed citations
16.
Marrack, Philippa, Jeremy Bender, Michael Jordan, et al.. (2001). Presidential Address to The American Association of Immunologists. The Journal of Immunology. 167(2). 617–621. 19 indexed citations
17.
Sun, Weiyong, Kamala Kesavan, Brian C. Schaefer, et al.. (2001). MEKK2 Associates with the Adapter Protein Lad/RIBP and Regulates the MEK5-BMK1/ERK5 Pathway. Journal of Biological Chemistry. 276(7). 5093–5100. 130 indexed citations
18.
Schaefer, Brian C., Margaret F. Ware, Philippa Marrack, et al.. (1999). Live Cell Fluorescence Imaging of T Cell MEKK2. Immunity. 11(4). 411–421. 49 indexed citations
19.
Schaefer, Brian C.. (1997). Gene cloning and analysis : current innovations. 9 indexed citations
20.
Schaefer, Brian C., et al.. (1997). Constitutive Activation of Epstein-Barr Virus (EBV) Nuclear Antigen 1 Gene Transcription by IRF1 and IRF2 during Restricted EBV Latency. Molecular and Cellular Biology. 17(2). 873–886. 62 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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