IG Young

2.5k total citations · 1 hit paper
27 papers, 2.1k citations indexed

About

IG Young is a scholar working on Immunology, Molecular Biology and Genetics. According to data from OpenAlex, IG Young has authored 27 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Immunology, 7 papers in Molecular Biology and 6 papers in Genetics. Recurrent topics in IG Young's work include Immune Cell Function and Interaction (12 papers), Virus-based gene therapy research (5 papers) and Asthma and respiratory diseases (5 papers). IG Young is often cited by papers focused on Immune Cell Function and Interaction (12 papers), Virus-based gene therapy research (5 papers) and Asthma and respiratory diseases (5 papers). IG Young collaborates with scholars based in Australia, United Kingdom and United States. IG Young's co-authors include HD Campbell, Colin J. Sanderson, Angel F. López, M A Vadas, Jennifer R. Gamble, AJ Hapel, Andrew J. Hapel, S. Ymer, William Q. J. Tucker and Honami Naora and has published in prestigious journals such as Nature, Nucleic Acids Research and The Journal of Experimental Medicine.

In The Last Decade

IG Young

27 papers receiving 2.0k citations

Hit Papers

Recombinant human interleukin 5 is a selective activator ... 1988 2026 2000 2013 1988 250 500 750
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Recombinant human interleukin 5 is a selective activator of human eosinophil function.
    1988 809 citations Angel F. López, Colin J. Sanderson et al. The Journal of Experimental Medicine profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
IG Young Australia 19 1.0k 766 418 310 273 27 2.1k
P F Weller United States 18 1.1k 1.1× 667 0.9× 381 0.9× 343 1.1× 562 2.1× 26 2.3k
Joel Tocker United States 21 1.7k 1.6× 620 0.8× 259 0.6× 206 0.7× 170 0.6× 32 2.3k
HD Campbell Australia 7 542 0.5× 588 0.8× 258 0.6× 249 0.8× 201 0.7× 8 1.3k
CJ Sanderson Australia 11 1.3k 1.2× 1.2k 1.6× 272 0.7× 419 1.4× 731 2.7× 14 2.6k
Arnold I. Levinson United States 27 1.2k 1.2× 240 0.3× 320 0.8× 235 0.8× 267 1.0× 89 2.4k
Ralph Giorno United States 24 924 0.9× 254 0.3× 374 0.9× 279 0.9× 444 1.6× 54 2.0k
R S Geha United States 24 1.2k 1.1× 407 0.5× 383 0.9× 525 1.7× 124 0.5× 34 2.3k
Omar Duramad United States 14 2.3k 2.2× 537 0.7× 605 1.4× 431 1.4× 311 1.1× 19 3.2k
François Fossiez France 19 2.8k 2.7× 506 0.7× 520 1.2× 203 0.7× 491 1.8× 24 3.9k
T Otsuka Japan 21 1.3k 1.3× 214 0.3× 614 1.5× 149 0.5× 236 0.9× 53 2.5k

Countries citing papers authored by IG Young

Since Specialization
Citations

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

Fields of papers citing papers by IG Young

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of IG Young

This figure shows the co-authorship network connecting the top 25 collaborators of IG Young. A scholar is included among the top collaborators of IG Young 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 IG Young. IG Young 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.
Young, IG, et al.. (2007). Eosinophilic inflammation: mechanisms regulating IL‐5 transcription in human T lymphocytes. Allergy. 62(10). 1131–1138. 11 indexed citations
2.
Robertson, Sarah A., et al.. (2000). Uterine eosinophils and reproductive performance in interleukin 5-deficient mice. Reproduction. 120(2). 423–432. 24 indexed citations
3.
Stevceva, Liljana, et al.. (2000). Eosinophilia is attenuated in experimental colitis induced in IL-5 deficient mice. Genes and Immunity. 1(3). 213–218. 30 indexed citations
4.
Simeonovic, Charmaine J., Michelle J. Townsend, J. Dennis Wilson, et al.. (1997). Eosinophils are not required for the rejection of neovascularized fetal pig proislet xenografts in mice. The Journal of Immunology. 158(5). 2490–2499. 38 indexed citations
5.
Campbell, HD, et al.. (1995). Localization of the inducible enhancer in the mouse interleukin-5 gene that is responsive to T-cell receptor stimulation. Blood. 85(8). 2069–2077. 18 indexed citations
6.
Naora, Honami, Joseph G. Altin, & IG Young. (1994). TCR-dependent and -independent signaling mechanisms differentially regulate lymphokine gene expression in the murine T helper clone D10.G4.1.. The Journal of Immunology. 152(12). 5691–5702. 47 indexed citations
7.
Wang, Yi, Hugh D. Campbell, & IG Young. (1993). Sex hormones and dexamethasone modulate interleukin-5 gene expression in T lymphocytes. The Journal of Steroid Biochemistry and Molecular Biology. 44(3). 203–210. 60 indexed citations
8.
Ingley, Evan & IG Young. (1991). Characterization of a receptor for interleukin-5 on human eosinophils and the myeloid leukemia line HL-60. Blood. 78(2). 339–344. 2 indexed citations
9.
10.
11.
López, Angel F., Colin J. Sanderson, Jennifer R. Gamble, et al.. (1988). Recombinant human interleukin 5 is a selective activator of human eosinophil function.. The Journal of Experimental Medicine. 167(1). 219–224. 809 indexed citations breakdown →
12.
Sutherland, GR, HD Campbell, IG Young, et al.. (1988). Interleukin-5 is at 5q31 and is deleted in the 5q- syndrome. Blood. 71(4). 1150–1152. 8 indexed citations
13.
Haig, David M., et al.. (1988). Rat IL-3 stimulates the growth of rat mucosal mast cells in culture.. PubMed. 65(2). 205–11. 33 indexed citations
14.
Ceredig, Rhodri, T. Robins, HD Campbell, IG Young, & AJ Hapel. (1988). Correlation of Interleukin-2 Receptor Expression With Tissue-Specific Growth of an Interleukin-3-Dependent Autocrine Leukemia. JNCI Journal of the National Cancer Institute. 80(3). 165–170. 3 indexed citations
15.
Sutherland, GR, Elizabeth Baker, HD Campbell, et al.. (1988). Interleukin-5 is at 5q31 and is deleted in the 5q- syndrome. Blood. 71(4). 1150–1152. 74 indexed citations
16.
Hodgkin, Philip D., Andrew J. Hapel, Raymond M. Johnson, IG Young, & K. J. Lafferty. (1987). BLOCKING OF DELIVERY OF THE ANTIGEN-MEDIATED SIGNAL TO THE NUCLEUS OF T CELLS BY CYCLOSPORINS. Transplantation. 43(5). 685–691. 15 indexed citations
17.
Cohén, Donna, Andrew J. Hapel, & IG Young. (1986). Clong and expression of the rat interleukin-3 gene. Nucleic Acids Research. 14(9). 3641–3658. 71 indexed citations
18.
19.
Ymer, S., William Q. J. Tucker, Colin J. Sanderson, et al.. (1985). Constitutive synthesis of interleukin-3 by leukaemia cell line WEHI-3B is due to retroviral insertion near the gene. Nature. 317(6034). 255–258. 268 indexed citations
20.
Hapel, AJ, et al.. (1985). Biologic properties of molecularly cloned and expressed murine interleukin-3. Blood. 65(6). 1453–1459. 77 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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