GE Shafer

662 total citations
10 papers, 544 citations indexed

About

GE Shafer is a scholar working on Genetics, Molecular Biology and Immunology. According to data from OpenAlex, GE Shafer has authored 10 papers receiving a total of 544 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Genetics, 6 papers in Molecular Biology and 4 papers in Immunology. Recurrent topics in GE Shafer's work include Virus-based gene therapy research (7 papers), Viral Infectious Diseases and Gene Expression in Insects (6 papers) and CRISPR and Genetic Engineering (3 papers). GE Shafer is often cited by papers focused on Virus-based gene therapy research (7 papers), Viral Infectious Diseases and Gene Expression in Insects (6 papers) and CRISPR and Genetic Engineering (3 papers). GE Shafer collaborates with scholars based in United States and Israel. GE Shafer's co-authors include R Cowherd, Jonathan Treisman, Zelig Eshhar, Steven A. Rosenberg, Patrick Hwu, James C. Yang, Patrick Hwu, G. Gross, Daniel Schindler and SA Rosenberg and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and Blood.

In The Last Decade

GE Shafer

8 papers receiving 532 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
GE Shafer United States 6 430 299 186 161 115 10 544
R. L. H. Bolhuis Netherlands 10 424 1.0× 397 1.3× 169 0.9× 133 0.8× 107 0.9× 15 585
E. Hart United States 7 232 0.5× 235 0.8× 89 0.5× 86 0.5× 108 0.9× 7 368
C. P. M. Ronteltap Netherlands 11 331 0.8× 428 1.4× 118 0.6× 80 0.5× 114 1.0× 15 560
Sarah A. Richman United States 12 502 1.2× 255 0.9× 156 0.8× 220 1.4× 118 1.0× 14 702
Daniel T. Harris United States 10 462 1.1× 319 1.1× 131 0.7× 173 1.1× 76 0.7× 13 578
Maria Moeller Australia 10 506 1.2× 356 1.2× 187 1.0× 135 0.8× 41 0.4× 11 574
Erica M. Gomes United States 7 379 0.9× 204 0.7× 148 0.8× 144 0.9× 21 0.2× 12 485
Elisa Kieback Germany 10 544 1.3× 444 1.5× 273 1.5× 185 1.1× 28 0.2× 15 697
M. E. M. Weijtens Netherlands 6 363 0.8× 254 0.8× 137 0.7× 62 0.4× 78 0.7× 6 391
Thomas Shum United States 10 476 1.1× 198 0.7× 177 1.0× 172 1.1× 48 0.4× 17 612

Countries citing papers authored by GE Shafer

Since Specialization
Citations

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

Fields of papers citing papers by GE Shafer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by GE Shafer. 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 GE Shafer. The network helps show where GE Shafer may publish in the future.

Co-authorship network of co-authors of GE Shafer

This figure shows the co-authorship network connecting the top 25 collaborators of GE Shafer. A scholar is included among the top collaborators of GE Shafer 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 GE Shafer. GE Shafer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
Shimada, Hideaki, David W. Emery, GE Shafer, et al.. (1996). Miniature swine MHC class II heterodimers expressed through double-copy retroviral vectors.. PubMed. 28(3). 1986–9. 1 indexed citations
2.
LeGuern, Christian, Hideaki Shimada, David W. Emery, et al.. (1995). Retrovirus-mediated transfer of MHC class II cDNA into swine bone marrow cells. Journal of Molecular Medicine. 73(6). 15 indexed citations
3.
Treisman, Jonathan, Patrick Hwu, Seijiro Minamoto, et al.. (1995). Interleukin-2-transduced lymphocytes grow in an autocrine fashion and remain responsive to antigen. Blood. 85(1). 139–145. 65 indexed citations
4.
Hwu, Patrick, James C. Yang, R Cowherd, et al.. (1995). In vivo antitumor activity of T cells redirected with chimeric antibody/T-cell receptor genes.. PubMed. 55(15). 3369–73. 226 indexed citations
6.
Hwu, Patrick, GE Shafer, Jonathan Treisman, et al.. (1993). Lysis of ovarian cancer cells by human lymphocytes redirected with a chimeric gene composed of an antibody variable region and the Fc receptor gamma chain.. The Journal of Experimental Medicine. 178(1). 361–366. 207 indexed citations
7.
Emery, David W., Charles V. Smith, GE Shafer, et al.. (1993). Expression of allogeneic class II cDNA in swine peripheral blood mononuclear cells following retroviral-mediated gene transfer into bone marrow.. PubMed. 25(1 Pt 1). 140–1. 1 indexed citations
9.
Emery, David W., GE Shafer, Evelyn M. Karson, David H. Sachs, & Christian LeGuern. (1992). Expression of allogeneic class II cDNA in swine bone marrow cells transduced with a recombinant retrovirus.. PubMed. 24(2). 468–9.
10.
Shafer, GE, David W. Emery, Kenth Gustafsson, et al.. (1991). Expression of a swine class II gene in murine bone marrow hematopoietic cells by retroviral-mediated gene transfer.. Proceedings of the National Academy of Sciences. 88(21). 9760–9764. 15 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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