John Shine

20.3k total citations · 6 hit papers
172 papers, 17.0k citations indexed

About

John Shine is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Genetics. According to data from OpenAlex, John Shine has authored 172 papers receiving a total of 17.0k indexed citations (citations by other indexed papers that have themselves been cited), including 100 papers in Molecular Biology, 59 papers in Cellular and Molecular Neuroscience and 23 papers in Genetics. Recurrent topics in John Shine's work include Neuropeptides and Animal Physiology (56 papers), Receptor Mechanisms and Signaling (45 papers) and RNA and protein synthesis mechanisms (17 papers). John Shine is often cited by papers focused on Neuropeptides and Animal Physiology (56 papers), Receptor Mechanisms and Signaling (45 papers) and RNA and protein synthesis mechanisms (17 papers). John Shine collaborates with scholars based in Australia, United States and Germany. John Shine's co-authors include L. Dalgarno, Howard M. Goodman, Yvonne Hort, John D. Baxter, Lisa Selbie, Herbert Herzog, Geoffrey L. Greene, Joseph Martial, Barry G. Rolfe and Andrew Baker and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

John Shine

169 papers receiving 15.8k citations

Hit Papers

The 3′-Terminal Sequence of Escherichia coli 16S Ribosoma... 1974 2026 1991 2008 1974 1975 1977 1986 1988 1000 2.0k 3.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Shine Australia 59 10.1k 5.0k 2.8k 1.6k 1.6k 172 17.0k
William B. Guggino United States 75 13.5k 1.3× 4.7k 0.9× 2.3k 0.8× 476 0.3× 990 0.6× 248 22.4k
Jerry B. Lingrel United States 73 13.5k 1.3× 1.7k 0.3× 1.5k 0.5× 1.4k 0.8× 819 0.5× 254 17.4k
Jack E. Dixon United States 99 24.8k 2.5× 4.3k 0.9× 3.9k 1.4× 1.2k 0.8× 2.9k 1.8× 347 35.7k
Hiroto Okayama Japan 53 14.4k 1.4× 3.1k 0.6× 1.7k 0.6× 518 0.3× 1.0k 0.7× 136 20.7k
Guy Haegeman Belgium 66 8.0k 0.8× 2.3k 0.5× 968 0.3× 998 0.6× 838 0.5× 179 16.7k
Michael A. Frohman United States 70 13.5k 1.3× 2.0k 0.4× 1.8k 0.6× 511 0.3× 1.5k 0.9× 161 19.1k
Masami Muramatsu Japan 74 12.9k 1.3× 5.3k 1.1× 722 0.3× 1.2k 0.8× 1.3k 0.8× 321 18.7k
Mark Donowitz United States 70 10.2k 1.0× 1.6k 0.3× 1.2k 0.4× 710 0.4× 660 0.4× 352 18.1k
William B. Pratt United States 82 16.1k 1.6× 4.9k 1.0× 1.2k 0.4× 3.0k 1.9× 442 0.3× 208 21.2k
Michael N. Hall Switzerland 108 34.3k 3.4× 3.7k 0.7× 1.8k 0.6× 959 0.6× 3.4k 2.2× 246 44.9k

Countries citing papers authored by John Shine

Since Specialization
Citations

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

Fields of papers citing papers by John Shine

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Shine

This figure shows the co-authorship network connecting the top 25 collaborators of John Shine. A scholar is included among the top collaborators of John Shine 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 John Shine. John Shine 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.
Hort, Yvonne, Chirag Patel, John A. Sayer, et al.. (2025). PKD1 5’UTR variants are a rare cause of disease in ADPKD and suggest a new focus for therapeutic development. European Journal of Human Genetics. 34(1). 61–69. 1 indexed citations
2.
Mallawaarachchi, Amali, Yvonne Hort, Kitty Lo, et al.. (2024). Somatic mutation in autosomal dominant polycystic kidney disease revealed by deep sequencing human kidney cysts. npj Genomic Medicine. 9(1). 69–69.
3.
Hort, Yvonne, Patricia A. Sullivan, Lindsay Fowles, et al.. (2023). Atypical splicing variants in PKD1 explain most undiagnosed typical familial ADPKD. npj Genomic Medicine. 8(1). 16–16. 8 indexed citations
4.
Mallawaarachchi, Amali, Ben Lundie, Yvonne Hort, et al.. (2021). Genomic diagnostics in polycystic kidney disease: an assessment of real-world use of whole-genome sequencing. European Journal of Human Genetics. 29(5). 760–770. 30 indexed citations
5.
Mallawaarachchi, Amali, Timothy J. Furlong, John Shine, Peter C. Harris, & Mark J. Cowley. (2018). Population data improves variant interpretation in autosomal dominant polycystic kidney disease. Genetics in Medicine. 21(6). 1425–1434. 7 indexed citations
6.
Doyle, Kharen L., Yvonne Hort, Herbert Herzog, & John Shine. (2012). Neuropeptide Y and peptide YY have distinct roles in adult mouse olfactory neurogenesis. Journal of Neuroscience Research. 90(6). 1126–1135. 17 indexed citations
7.
Henderson, N. Kathryn, et al.. (1999). A polymorphism in the human GALR3 galanin receptor gene (GALNR3). Molecular and Cellular Probes. 13(4). 325–327. 8 indexed citations
8.
Ormandy, Christopher J., et al.. (1998). Amplification, expression, and steroid regulation of the preprogalanin gene in human breast cancer.. PubMed. 58(7). 1353–7. 17 indexed citations
9.
Kofler, Barbara, et al.. (1995). Characterization of the 5′-Flanking Region of the Human Preprogalanin Gene. DNA and Cell Biology. 14(4). 321–329. 34 indexed citations
10.
Selbie, Lisa, Gillian R. Hayes, & John Shine. (1989). The Major Dopamine D2 Receptor: Molecular Analysis of the Human D2 A Subtype. DNA. 8(9). 683–689. 79 indexed citations
11.
Alexander, Ian E., Christine L. Clarke, John Shine, & Robert L. Sutherland. (1989). Progestin Inhibition of Progesterone Receptor Gene Expression in Human these steroids is determined in part by the cellular Breast Cancer Cells. Molecular Endocrinology. 3(9). 1377–1386. 105 indexed citations
12.
Baker, Andrew R. & John Shine. (1985). Human Kidney Kallikrein: cDNA Cloning and Sequence Analysis. DNA. 4(6). 445–450. 76 indexed citations
13.
Hort, Yvonne, Daniel F. Catanzaro, Judy Tellam, et al.. (1984). Primary Structure of the Human Renin Gene. DNA. 3(6). 457–468. 99 indexed citations
14.
Schofield, Peter R., Robert W. Ridge, Barry G. Rolfe, John Shine, & John M. Watson. (1984). Host-specific nodulation is encoded on a 14kb DNA fragment in Rhizobium trifolii. Plant Molecular Biology. 3(1). 3–11. 68 indexed citations
15.
Scott, Kieran F., Barry G. Rolfe, & John Shine. (1983). Nitrogenase Structural Genes Are Unlinked in the Nonlegume Symbiont Parasponia Rhizobium. DNA. 2(2). 141–148. 43 indexed citations
16.
Scott, Kieran F., Barry G. Rolfe, & John Shine. (1983). Biological Nitrogen Fixation: Primary Structure of the Rhizobium trifolii Iron Protein Gene. DNA. 2(2). 149–155. 56 indexed citations
17.
Haley, John D., Peter J. Hudson, Denis B. Scanlon, et al.. (1982). Porcine Relaxin: Molecular Cloning and cDNA Structure. DNA. 1(2). 155–162. 57 indexed citations
19.
Whitfeld, Peter L, P. H. Seeburg, & John Shine. (1982). The Human Pro-opiomelanocortin Gene: Organization, Sequence, and Interspersion with Repetitive DNA. DNA. 1(2). 133–143. 123 indexed citations
20.
Seeburg, P. H., John Shine, Joseph Martial, et al.. (1979). Structure of growth hormone gene sequences and their expression in bacteria and in cultured cells. Open Repository and Bibliography (University of Liège). 2 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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