Stephen M. Shaw

1.9k total citations
39 papers, 1.0k citations indexed

About

Stephen M. Shaw is a scholar working on Molecular Biology, Immunology and Epidemiology. According to data from OpenAlex, Stephen M. Shaw has authored 39 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 12 papers in Immunology and 7 papers in Epidemiology. Recurrent topics in Stephen M. Shaw's work include Immune Cell Function and Interaction (6 papers), Immunotherapy and Immune Responses (6 papers) and Monoclonal and Polyclonal Antibodies Research (5 papers). Stephen M. Shaw is often cited by papers focused on Immune Cell Function and Interaction (6 papers), Immunotherapy and Immune Responses (6 papers) and Monoclonal and Polyclonal Antibodies Research (5 papers). Stephen M. Shaw collaborates with scholars based in United States, United Kingdom and Netherlands. Stephen M. Shaw's co-authors include William E. Biddison, G M Shearer, David H. Smith, Peter M.T. Deen, Yuedan Li, Mike Westby, Chris Pickford, Patrick Anderson, Arnold L. Smith and Alain Vandewalle and has published in prestigious journals such as Journal of Clinical Investigation, The Journal of Experimental Medicine and Journal of Clinical Oncology.

In The Last Decade

Stephen M. Shaw

39 papers receiving 960 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen M. Shaw United States 17 356 256 219 159 145 39 1.0k
Margaret Nelson Australia 25 300 0.8× 604 2.4× 260 1.2× 198 1.2× 39 0.3× 66 1.5k
V J Merluzzi United States 14 297 0.8× 552 2.2× 162 0.7× 246 1.5× 76 0.5× 27 1.4k
Vincent Holl France 18 373 1.0× 384 1.5× 100 0.5× 97 0.6× 55 0.4× 32 1.0k
J A Kant United States 20 585 1.6× 350 1.4× 225 1.0× 65 0.4× 402 2.8× 31 1.7k
Takemitsu Nagahata Japan 15 515 1.4× 128 0.5× 229 1.0× 111 0.7× 29 0.2× 24 906
Adan Rios United States 15 235 0.7× 382 1.5× 136 0.6× 130 0.8× 124 0.9× 67 1.2k
Arevik Mosoian United States 19 215 0.6× 314 1.2× 327 1.5× 211 1.3× 34 0.2× 25 1.1k
Christiane Thallinger Austria 25 876 2.5× 248 1.0× 101 0.5× 66 0.4× 206 1.4× 56 1.7k
Lauriane Goldwirt France 19 259 0.7× 63 0.2× 130 0.6× 204 1.3× 71 0.5× 53 1.1k
Shiro Shibayama Japan 13 310 0.9× 662 2.6× 80 0.4× 206 1.3× 34 0.2× 26 1.2k

Countries citing papers authored by Stephen M. Shaw

Since Specialization
Citations

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

Fields of papers citing papers by Stephen M. Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen M. Shaw. 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 Stephen M. Shaw. The network helps show where Stephen M. Shaw may publish in the future.

Co-authorship network of co-authors of Stephen M. Shaw

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen M. Shaw. A scholar is included among the top collaborators of Stephen M. Shaw 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 Stephen M. Shaw. Stephen M. Shaw 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.
Shaw, Stephen M., Kim Wigglesworth, Oliver Schulz, et al.. (2019). AGI-134: a fully synthetic α-Gal glycolipid that converts tumors into in situ autologous vaccines, induces anti-tumor immunity and is synergistic with an anti-PD-1 antibody in mouse melanoma models. Cancer Cell International. 19(1). 346–346. 12 indexed citations
2.
3.
Brown, Derek B., et al.. (2016). Safety Notables: Information from the Literature. Organic Process Research & Development. 20(3). 575–582. 5 indexed citations
4.
Kristian, Sascha A., Stephen M. Shaw, Kim Wigglesworth, et al.. (2016). AGI-134, a fully synthetic α-Gal-based cancer immunotherapy: Synergy with an anti-PD-1 antibody and pre-clinical pharmacokinetic and toxicity profiles.. Journal of Clinical Oncology. 34(15_suppl). 3083–3083. 2 indexed citations
5.
Dale, David C., et al.. (2014). Safety Notables: Information from the Literature. Organic Process Research & Development. 18(12). 1778–1785. 1 indexed citations
6.
Hurley, Amanda, Mindy Smith, Tatiana Karpova, et al.. (2012). Enhanced Effector Function of CD8+ T Cells From Healthy Controls and HIV-Infected Patients Occurs Through Thrombin Activation of Protease-Activated Receptor 1. The Journal of Infectious Diseases. 207(4). 638–650. 35 indexed citations
7.
Barnhart, Richard W., et al.. (2012). Safety Notables: Information from the Literature. Organic Process Research & Development. 16(12). 1980–1985. 2 indexed citations
8.
Pickford, Chris, Frauke Christ, Stephen M. Shaw, et al.. (2011). Pre-clinical evaluation of HIV replication inhibitors that target the HIV-integrase-LEDGF/p75 interaction. Journal of the International AIDS Society. 15. 26–27. 3 indexed citations
9.
Shaw, Stephen M., et al.. (2011). Colony-forming assays reveal enhanced suppression of hepatitis C virus replication using combinations of direct-acting antivirals. Journal of Virological Methods. 174(1-2). 153–157. 11 indexed citations
10.
11.
Li, Yuedan, Stephen M. Shaw, Erik‐Jan Kamsteeg, Alain Vandewalle, & Peter M.T. Deen. (2006). Development of Lithium-Induced Nephrogenic Diabetes Insipidus Is Dissociated from Adenylyl Cyclase Activity. Journal of the American Society of Nephrology. 17(4). 1063–1072. 81 indexed citations
12.
Shaw, Stephen M., et al.. (2000). What the WTO Really Means for China. The McKinsey Quarterly. 128. 4 indexed citations
13.
Shaw, Stephen M., et al.. (1993). "Second Generation" MNCs in China. The McKinsey Quarterly. 3. 24 indexed citations
14.
Shaw, Stephen M. & Jonathan Woetzel. (1992). A Fresh Look at China. The McKinsey Quarterly. 91(3). 37–e13479. 4 indexed citations
15.
Hall, Russell P., et al.. (1989). Alterations in HLA-DP and HLA-DQ Antigen Frequency in Patients with Dermatitis Herpetiformis. Journal of Investigative Dermatology. 93(4). 501–505. 45 indexed citations
16.
Biddison, William E. & Stephen M. Shaw. (1989). CD4 Expression and Function in HLA Class Il‐Specific T Cells. Immunological Reviews. 109(1). 5–15. 16 indexed citations
17.
Shaw, Stephen M., et al.. (1983). In vitro generation of cytotoxic cells specific for human minor histocompatibility antigens by lymphocytes from a normal donor potentially primed during pregnancy.. The Journal of Experimental Medicine. 157(6). 2172–2177. 18 indexed citations
18.
Biddison, William E., Susan Payne, G M Shearer, & Stephen M. Shaw. (1980). Human cytotoxic T cell responses to trinitrophenyl hapten and influenza virus. Diversity of restriction antigens and specificity of HLA-linked genetic regulation.. PubMed. 152(2 Pt 2). 204s–217s. 19 indexed citations
19.
Anderson, Porter, et al.. (1980). Phenotypic and Genetic Variation in the Susceptibility of Haemophilus influenzae Type b to Antibodies to Somatic Antigens. Journal of Clinical Investigation. 65(4). 885–891. 70 indexed citations
20.
Shaw, Stephen M., et al.. (1979). HLA restriction of human influenza virus-immune cytotoxic T cells.. PubMed. 11(4). 1845–8. 1 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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