S K Narula

1.2k total citations
24 papers, 983 citations indexed

About

S K Narula is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, S K Narula has authored 24 papers receiving a total of 983 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Immunology, 8 papers in Molecular Biology and 6 papers in Oncology. Recurrent topics in S K Narula's work include Immune Cell Function and Interaction (7 papers), Monoclonal and Polyclonal Antibodies Research (6 papers) and interferon and immune responses (4 papers). S K Narula is often cited by papers focused on Immune Cell Function and Interaction (7 papers), Monoclonal and Polyclonal Antibodies Research (6 papers) and interferon and immune responses (4 papers). S K Narula collaborates with scholars based in United States, United Kingdom and Japan. S K Narula's co-authors include Paul D. Robbins, Michael T. Lotze, Hideaki Tahara, Tomonari Suzuki, Hiroyuki Tahara, Robert Berman, Chin-Cheng Chou, Stephen R. Indelicato, Takashi Suzuki and Kevin W. Moore and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Experimental Medicine and Blood.

In The Last Decade

S K Narula

23 papers receiving 938 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S K Narula United States 14 671 288 215 113 107 24 983
A.D. Donnenberg United States 16 618 0.9× 264 0.9× 204 0.9× 69 0.6× 144 1.3× 38 1.2k
Marcus Pericin Switzerland 11 1.0k 1.5× 423 1.5× 288 1.3× 92 0.8× 119 1.1× 13 1.3k
Theresa Truitt United States 10 1.0k 1.6× 356 1.2× 255 1.2× 100 0.9× 163 1.5× 10 1.4k
J Zeromski Poland 19 537 0.8× 255 0.9× 265 1.2× 55 0.5× 159 1.5× 98 1.2k
Eugene C. Butcher United States 7 1.0k 1.5× 269 0.9× 187 0.9× 113 1.0× 67 0.6× 9 1.4k
Katja C. Beier Germany 9 1.3k 1.9× 355 1.2× 135 0.6× 131 1.2× 79 0.7× 11 1.6k
Patricia E. Korty United States 5 1.1k 1.7× 196 0.7× 186 0.9× 109 1.0× 71 0.7× 6 1.3k
J R Keller United States 15 561 0.8× 296 1.0× 484 2.3× 105 0.9× 64 0.6× 19 1.2k
JE de Vries United States 14 687 1.0× 156 0.5× 168 0.8× 51 0.5× 75 0.7× 25 1.1k
Dario Magaletti United States 11 853 1.3× 152 0.5× 200 0.9× 71 0.6× 67 0.6× 14 1.1k

Countries citing papers authored by S K Narula

Since Specialization
Citations

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

Fields of papers citing papers by S K Narula

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S K Narula. 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 S K Narula. The network helps show where S K Narula may publish in the future.

Co-authorship network of co-authors of S K Narula

This figure shows the co-authorship network connecting the top 25 collaborators of S K Narula. A scholar is included among the top collaborators of S K Narula 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 S K Narula. S K Narula 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.
Biswas, Kajal, Alexander Y. Mitrophanov, Sounak Sahu, et al.. (2023). Sequencing-based functional assays for classification of BRCA2 variants in mouse ESCs. Cell Reports Methods. 3(11). 100628–100628. 1 indexed citations
2.
Es, Inge E. van, Jay S. Fine, Mark A. Smith, et al.. (2013). OP0304 BTK Inhibition Suppresses Inflammatory Cytokine Production and Affects Gene Expression in Human Macrophages and RA Synovial Tissue Explants. Annals of the Rheumatic Diseases. 72. A157–A157.
3.
Chin, Jia En, S Seeber, Jens Niewoehner, et al.. (2012). TL1A/TNFSF15 directly induces proinflammatory cytokines, including TNFα, from CD3+CD161+ T cells to exacerbate gut inflammation. Mucosal Immunology. 6(5). 886–899. 57 indexed citations
4.
Fu, Fen, Liwei Lu, S K Narula, et al.. (1999). Recipient pretreatment with mammalian IL-10 prolongs mouse cardiac allograft survival by inhibition of anti-donor T cell responses. Transplantation Proceedings. 31(1-2). 115–115. 9 indexed citations
5.
Narula, S K, David L. Cutler, & Paul Grint. (1998). Immunomodulation of Crohn’s disease by Interleukin-10. Birkhäuser Basel eBooks. 49. 57–65. 14 indexed citations
6.
7.
Moine, Olivier Le, H Louis, Eric Quertinmont, et al.. (1998). Donor pretreatment with IL-10 decreases TNF, IFN-gamma release and liver injury after cold ischemia-reperfusion in mice. Gastroenterology. 114. A1287–A1287. 1 indexed citations
8.
9.
Mikulowska, Anna, et al.. (1996). Interleukin‐10 Suppresses the Development of Collagen Type II‐Induced Arthritis and Ameliorates Sustained Arthritis in Rats. Scandinavian Journal of Immunology. 44(6). 607–614. 88 indexed citations
10.
Berman, Robert, Tomonari Suzuki, Hiroyuki Tahara, et al.. (1996). Systemic administration of cellular IL-10 induces an effective, specific, and long-lived immune response against established tumors in mice. The Journal of Immunology. 157(1). 231–238. 169 indexed citations
11.
Suzuki, Takashi, Hideaki Tahara, S K Narula, et al.. (1995). Viral interleukin 10 (IL-10), the human herpes virus 4 cellular IL-10 homologue, induces local anergy to allogeneic and syngeneic tumors.. The Journal of Experimental Medicine. 182(2). 477–486. 157 indexed citations
12.
Konieczny, Bogumila T., et al.. (1995). Interleukin-10 eliminates anti-CD3 monoclonal antibody-induced mortality and prolongs heart allograft survival in inbred mice.. PubMed. 27(1). 392–4. 17 indexed citations
13.
Bober, Loretta A., et al.. (1995). IL-4 induces neutrophilic maturation of HL-60 cells and activation of human peripheral blood neutrophils. Clinical & Experimental Immunology. 99(1). 129–136. 35 indexed citations
14.
Schwarz, Max, et al.. (1995). Interleukin 4 retards dissemination of a human B-cell lymphoma in severe combined immunodeficient mice.. PubMed. 55(17). 3692–6. 13 indexed citations
15.
Tan, Jimmy, et al.. (1993). Characterization of interleukin-10 receptors on human and mouse cells.. Journal of Biological Chemistry. 268(28). 21053–21059. 128 indexed citations
16.
Lunn, Charles A., James Fossetta, David C. Dalgarno, et al.. (1992). A point mutation of human interferon γ abolishes receptor recognition. Protein Engineering Design and Selection. 5(3). 253–257. 20 indexed citations
17.
Lunn, Charles A., et al.. (1992). A point mutation that decreases the thermal stability of human interferon γ. Protein Engineering Design and Selection. 5(3). 249–252. 6 indexed citations
18.
Lundell, D J, Charles A. Lunn, Robert S. Greenberg, et al.. (1990). Exploiting the cell membrane for the production of heterologous proteins in Escherichia coli. Biotechnology and Applied Biochemistry. 12(5). 567–578. 3 indexed citations
19.
Narula, S K, et al.. (1990). Cloning and characterization of a vertebrate cellular myosin regulatory light chain complementary DNA.. Circulation Research. 67(4). 933–940. 3 indexed citations
20.
Narula, S K, et al.. (1988). Alterations of the Amino Terminus of Murine Interferon-γ: Expression and Biological Activity. Journal of Interferon Research. 8(4). 483–494. 8 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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