G E Wu

2.0k total citations · 1 hit paper
27 papers, 1.6k citations indexed

About

G E Wu is a scholar working on Immunology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, G E Wu has authored 27 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Immunology, 12 papers in Molecular Biology and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in G E Wu's work include T-cell and B-cell Immunology (13 papers), Immune Cell Function and Interaction (9 papers) and Glycosylation and Glycoproteins Research (6 papers). G E Wu is often cited by papers focused on T-cell and B-cell Immunology (13 papers), Immune Cell Function and Interaction (9 papers) and Glycosylation and Glycoproteins Research (6 papers). G E Wu collaborates with scholars based in Canada, United States and China. G E Wu's co-authors include Christopher J. Paige, Scott R. McKercher, Ann J. Feeney, Hélène Baribault, Bruce E. Torbett, Gregory W. Henkel, R. Maki, M Klemsz, Deborah J. Vestal and Kenton L. Anderson and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and The Journal of Experimental Medicine.

In The Last Decade

G E Wu

27 papers receiving 1.6k citations

Hit Papers

Targeted disruption of the PU.1 gene results in multiple ... 1996 2026 2006 2016 1996 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
G E Wu Canada 17 1.0k 673 262 218 197 27 1.6k
Trisha Norton Tanzania 18 1.3k 1.3× 841 1.2× 146 0.6× 80 0.4× 366 1.9× 29 2.0k
Susanne Edelhoff United States 20 893 0.9× 866 1.3× 156 0.6× 167 0.8× 203 1.0× 35 1.9k
M Klemsz United States 13 1.3k 1.2× 1.4k 2.0× 384 1.5× 75 0.3× 575 2.9× 17 2.8k
Gregory W. Henkel United States 7 778 0.7× 885 1.3× 254 1.0× 28 0.1× 273 1.4× 8 1.7k
Domenica Saul Germany 18 517 0.5× 452 0.7× 161 0.6× 227 1.0× 355 1.8× 24 1.1k
Fredrick G. Karnell United States 14 935 0.9× 1.3k 1.9× 371 1.4× 72 0.3× 357 1.8× 16 2.2k
Kathy Strauch United States 9 919 0.9× 336 0.5× 95 0.4× 227 1.0× 173 0.9× 10 1.3k
Michael Deftos United States 12 661 0.6× 695 1.0× 71 0.3× 161 0.7× 177 0.9× 18 1.3k
Agneta Levinovitz Sweden 11 289 0.3× 465 0.7× 68 0.3× 94 0.4× 121 0.6× 12 1.0k
Dennis Bouchard Canada 9 1.5k 1.5× 1.2k 1.8× 79 0.3× 86 0.4× 615 3.1× 9 2.5k

Countries citing papers authored by G E Wu

Since Specialization
Citations

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

Fields of papers citing papers by G E Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G E Wu. 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 G E Wu. The network helps show where G E Wu may publish in the future.

Co-authorship network of co-authors of G E Wu

This figure shows the co-authorship network connecting the top 25 collaborators of G E Wu. A scholar is included among the top collaborators of G E Wu 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 G E Wu. G E Wu 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.
Li, Hua, et al.. (2024). The RhoGAP ARHGAP32 interacts with desmoplakin, and is required for desmosomal organization and assembly. Journal of Cell Science. 137(18). 2 indexed citations
2.
Dzneladze, Irakli, et al.. (2015). Functional analyses of polymorphic variants of human terminal deoxynucleotidyl transferase. Genes and Immunity. 16(6). 388–398. 3 indexed citations
3.
Ko, Kai‐Hsiung, et al.. (2007). Impaired V(D)J recombination and increased apoptosis among B cell precursors in the bone marrow of c-Abl-deficient mice. International Immunology. 19(3). 267–276. 18 indexed citations
4.
Gao, Ge, et al.. (2006). Identification of a novel HLA‐B allele HLA‐B*4059 in Chinese bone marrow donors†. Tissue Antigens. 67(4). 339–340. 2 indexed citations
5.
Larijani, Mani, et al.. (2005). Coding Joint Diversity in Mature and Immature B‐Cell Lines. Scandinavian Journal of Immunology. 62(s1). 114–118. 1 indexed citations
6.
Larijani, Mani, et al.. (1999). The role of components of recombination signal sequences in immunoglobulin gene segment usage: a V81x model. Nucleic Acids Research. 27(11). 2304–2309. 25 indexed citations
7.
Fanning, Liam J., F. E. Bertrand, C M Steinberg, & G E Wu. (1998). Molecular mechanisms involved in receptor editing at the Ig heavy chain locus.. International Immunology. 10(2). 241–246. 22 indexed citations
8.
Bertrand, F. E., et al.. (1997). Sequence of the RAG1 and RAG2 Intergenic Region inZebrafish (Danio rerio). Journal of Immunology Research. 5(3). 211–214. 2 indexed citations
9.
Yu, Chunlin, et al.. (1996). B and T cells are not required for the viable motheaten phenotype.. The Journal of Experimental Medicine. 183(2). 371–380. 62 indexed citations
10.
Guidos, Cynthia J., Carmen J. Williams, G E Wu, Christopher J. Paige, & Jayne S. Danska. (1995). Development of CD4+CD8+ thymocytes in RAG-deficient mice through a T cell receptor β chain-independent pathway.. The Journal of Experimental Medicine. 181(3). 1187–1195. 67 indexed citations
11.
Connor, Alison, Liam J. Fanning, Jakub W. Celler, et al.. (1995). Mouse VH7183 recombination signal sequences mediate recombination more frequently than those of VHJ558. The Journal of Immunology. 155(11). 5268–5272. 38 indexed citations
12.
Atkinson, Michael J. & G E Wu. (1993). Genomic sequence of a V(D)J rearrangement utilizing a new VH7183 family member VH7183.15. Molecular Immunology. 30(1). 109–110. 3 indexed citations
13.
Paige, Christopher J., Ana Cumano, Dale A. Ramsden, & G E Wu. (1992). The K:λ ratio and B-cell development in the foetal liver. Research in Immunology. 143(8). 822–824. 2 indexed citations
14.
Ramsden, Dale A. & G E Wu. (1992). The virgin b cell k:λ ratio. Research in Immunology. 143(8). 811–817. 4 indexed citations
15.
Chang, Yung, Christopher J. Paige, & G E Wu. (1992). Enumeration and characterization of DJH structures in mouse fetal liver.. The EMBO Journal. 11(5). 1891–1899. 87 indexed citations
16.
Atkinson, Michael J., et al.. (1991). Ig gene rearrangements on individual alleles of Abelson murine leukemia cell lines from (C57BL/6 x BALB/c) F1 fetal livers. The Journal of Immunology. 146(8). 2805–2812. 17 indexed citations
17.
Misener, Virginia L., et al.. (1990). Association of Ig L chain-like protein lambda 5 with a 16-kilodalton protein in mouse pre-B cell lines is not dependent on the presence of Ig H chain protein.. The Journal of Immunology. 145(3). 905–909. 29 indexed citations
18.
Wu, G E & Christopher J. Paige. (1988). VH gene family utilization is regulated by a locus outside of the VH region.. The Journal of Experimental Medicine. 167(4). 1499–1504. 32 indexed citations
19.
Benveniste, Patricia, et al.. (1988). A sensitive dot blot procedure for detecting mRNA in lymphoid cells grown in liquid culture. Journal of Immunological Methods. 107(2). 165–177. 5 indexed citations
20.
Hozumi, Nobumichi, G E Wu, Helios Murialdo, et al.. (1982). Arrangement of lambda light chain genes in mutant clones of the MOPC 315 mouse myeloma cells.. The Journal of Immunology. 129(1). 260–266. 18 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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