Gray D. Shaw
- Immunology and Allergy top 0.2%
- Cell Adhesion Molecules Research 19
- Transplantation top 1%
- Renal Transplantation Outcomes and Treatments 5
- Immunology top 1%
- Immune Response and Inflammation 8
- Molecular Biology top 1%
- RNA Interference and Gene Delivery 6
- Glycosylation and Glycoproteins Research 5
- Hematology top 1%
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- Organ Transplantation Techniques and Outcomes 15
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- Protease and Inhibitor Mechanisms 6
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- Monoclonal and Polyclonal Antibodies Research 5
- Co-authors
- Robert KamenRaymond T. CamphausenNicholas L. TilneyW.S. SomersJin TangKari C. NadeauDianne SakoK.M. Barone
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Gray D. Shaw
51 papers receiving 7.7k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Immunology and Allergy 1.5k
- Transplantation 373
- Immunology 2.2k
- Molecular Biology 4.1k
- Hematology 666
Countries citing papers authored by Gray D. Shaw
This map shows the geographic impact of Gray D. 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 Gray D. Shaw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gray D. Shaw more than expected).
Fields of papers citing papers by Gray D. Shaw
This network shows the impact of papers produced by Gray D. 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 Gray D. Shaw. The network helps show where Gray D. Shaw may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gray D. Shaw, 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 | 2020 | 6 | |
| 2 | Pillars article: a conserved AU sequence from the 3' untranslated region of GM-CSF mRNA mediates selective mRNA degradation. Cell. 1986. 46: 659-667. | 2012 | 5 |
| 3 | 2006 | 48 | |
| 4 | 2006 | 61 | |
| 5 | 2005 | 74 | |
| 6 | 2005 | 19 | |
| 7 | 2002 | 0 | |
| 8 | 2002 | 55 | |
| 9 | 2002 | 26 | |
| 10 | 2002 | 16 | |
| 11 | 2001 | 83 | |
| 12 | 2001 | 33 | |
| 13 | Insights into the Molecular Basis of Leukocyte Tethering and Rolling Revealed by Structures of P- and E-Selectin Bound to SLeX and PSGL-1breakdown → | 2000 | 612 |
| 14 | 1998 | 8 | |
| 15 | 1997 | 16 | |
| 16 | 1997 | 437 | |
| 17 | 1997 | 92 | |
| 18 | 1995 | 132 | |
| 19 | 1995 | 378 | |
| 20 | 1989 | 9 |
About Gray D. Shaw
Gray D. Shaw is a scholar working on Immunology and Allergy, Transplantation and Immunology, having authored 52 papers that have together received 8.0k indexed citations. Recurring topics across this work include Cell Adhesion Molecules Research (19 papers), Organ Transplantation Techniques and Outcomes (15 papers), Immune Response and Inflammation (8 papers), RNA Interference and Gene Delivery (6 papers), Protease and Inhibitor Mechanisms (6 papers), Glycosylation and Glycoproteins Research (5 papers), Renal Transplantation Outcomes and Treatments (5 papers) and Monoclonal and Polyclonal Antibodies Research (5 papers). The work is most often cited by research in Immunology and Allergy (1.5k citations), Transplantation (373 citations) and Immunology (2.2k citations). Gray D. Shaw has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Robert Kamen, Raymond T. Camphausen, Nicholas L. Tilney, W.S. Somers, Jin Tang, Kari C. Nadeau, Dianne Sako, K.M. Barone, Dale A. Cumming and M Takada. Their work appears in journals such as Transplantation, Cell, Blood, American Journal of Transplantation and Journal of Investigative Dermatology.
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.