Ian Brierley

7.5k total citations · 1 hit paper
83 papers, 5.5k citations indexed

About

Ian Brierley is a scholar working on Molecular Biology, Infectious Diseases and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Ian Brierley has authored 83 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Molecular Biology, 29 papers in Infectious Diseases and 29 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Ian Brierley's work include RNA and protein synthesis mechanisms (50 papers), Viral Infections and Immunology Research (29 papers) and Viral gastroenteritis research and epidemiology (24 papers). Ian Brierley is often cited by papers focused on RNA and protein synthesis mechanisms (50 papers), Viral Infections and Immunology Research (29 papers) and Viral gastroenteritis research and epidemiology (24 papers). Ian Brierley collaborates with scholars based in United Kingdom, South Sudan and United States. Ian Brierley's co-authors include Stephen Inglis, Andrew E. Firth, Sawsan Napthine, Paul Digard, Robert J.C. Gilbert, T. D. K. Brown, Simon Pennell, Olivier Namy, Tom Brown and Terence P. Herbert and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Ian Brierley

82 papers receiving 5.4k citations

Hit Papers

Characterization of an efficient coronavirus ribosomal fr... 1989 2026 2001 2013 1989 100 200 300 400 500
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. Characterization of an efficient coronavirus ribosomal frameshifting signal: Requirement for an RNA pseudoknot
    1989 555 citations Ian Brierley et al. profile →

Peers

Ian Brierley
Aniko V. Paul United States
Núria Verdaguer Spain
Vadim I. Agol Russia
Bert L. Semler United States
A.R. Bellamy New Zealand
Anette Schneemann United States
Cristina Risco Spain
Karla Kirkegaard United States
Margo A. Brinton United States
Sondra Schlesinger United States
Aniko V. Paul United States
Ian Brierley
Citations per year, relative to Ian Brierley Ian Brierley (= 1×) peers Aniko V. Paul

Countries citing papers authored by Ian Brierley

Since Specialization
Citations

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

Fields of papers citing papers by Ian Brierley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ian Brierley

This figure shows the co-authorship network connecting the top 25 collaborators of Ian Brierley. A scholar is included among the top collaborators of Ian Brierley 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 Ian Brierley. Ian Brierley 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.
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Dinan, Adam M., Shiho Torii, Hazel Stewart, et al.. (2024). Zika viruses encode 5′ upstream open reading frames affecting infection of human brain cells. Nature Communications. 15(1). 8822–8822. 2 indexed citations
3.
Busnadiego, Idoia, Sarah Keep, Katherine A. Brown, et al.. (2021). Manipulation of the unfolded protein response: A pharmacological strategy against coronavirus infection. PLoS Pathogens. 17(6). e1009644–e1009644. 54 indexed citations
4.
Hill, Chris H., Sawsan Napthine, Katherine A. Brown, et al.. (2021). Investigating molecular mechanisms of 2A-stimulated ribosomal pausing and frameshifting in Theilovirus. Nucleic Acids Research. 49(20). 11938–11958. 12 indexed citations
5.
Hill, Chris H., Sawsan Napthine, Andrew E. Firth, et al.. (2021). Structural and molecular basis for Cardiovirus 2A protein as a viral gene expression switch. Nature Communications. 12(1). 7166–7166. 24 indexed citations
6.
Chung, Betty, Martin Balcerowicz, Marco Di Antonio, et al.. (2020). An RNA thermoswitch regulates daytime growth in Arabidopsis. Nature Plants. 6(5). 522–532. 194 indexed citations
7.
Pearce, Sarah F., Miriam Cipullo, Betty Chung, Ian Brierley, & Joanna Rorbach. (2020). Mitoribosome Profiling from Human Cell Culture: A High Resolution View of Mitochondrial Translation. Methods in molecular biology. 2192. 183–196. 10 indexed citations
8.
Irigoyen, Nerea, Andrew E. Firth, Joshua D. Jones, et al.. (2016). High-Resolution Analysis of Coronavirus Gene Expression by RNA Sequencing and Ribosome Profiling. PLoS Pathogens. 12(2). e1005473–e1005473. 143 indexed citations
9.
Ren, Hongwei, Robert Valentine, Michela Mazzon, et al.. (2015). Inhibition of Translation Initiation by Protein 169: A Vaccinia Virus Strategy to Suppress Innate and Adaptive Immunity and Alter Virus Virulence. PLoS Pathogens. 11(9). e1005151–e1005151. 30 indexed citations
10.
Miyadera, Keiko, et al.. (2012). Multiple Mechanisms Contribute to Leakiness of a Frameshift Mutation in Canine Cone-Rod Dystrophy. PLoS ONE. 7(12). e51598–e51598. 10 indexed citations
11.
Napthine, Sawsan, et al.. (2009). Expression of the VP2 Protein of Murine Norovirus by a Translation Termination-Reinitiation Strategy. PLoS ONE. 4(12). e8390–e8390. 31 indexed citations
12.
Moran, Stephen, John F. Flanagan, Olivier Namy, et al.. (2008). The Mechanics of Translocation: A Molecular “Spring-and-Ratchet” System. Structure. 16(5). 664–672. 11 indexed citations
13.
Powell, Michael, Sawsan Napthine, Richard J. Jackson, Ian Brierley, & T. D. K. Brown. (2008). Characterization of the termination–reinitiation strategy employed in the expression of influenza B virus BM2 protein. RNA. 14(11). 2394–2406. 46 indexed citations
14.
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Namy, Olivier, Stephen Moran, David I. Stuart, Robert J.C. Gilbert, & Ian Brierley. (2006). A mechanical explanation of RNA pseudoknot function in programmed ribosomal frameshifting. Nature. 441(7090). 244–247. 228 indexed citations
16.
Brierley, Ian, et al.. (2003). V, 2.Ribosomal frameshifting in astroviruses. PubMed. 9. 587–606. 3 indexed citations
17.
Napthine, Sawsan, et al.. (2001). Ribosomal Pausing at a Frameshifter RNA Pseudoknot Is Sensitive to Reading Phase but Shows Little Correlation with Frameshift Efficiency. Molecular and Cellular Biology. 21(24). 8657–8670. 116 indexed citations
18.
Liphardt, Jan, et al.. (1999). Evidence for an RNA pseudoknot loop-helix interaction essential for efficient −1 ribosomal frameshifting. Journal of Molecular Biology. 288(3). 321–335. 62 indexed citations
19.
Herbert, Terence P., Ian Brierley, & T. D. K. Brown. (1996). Detection of the ORF3 polypeptide of feline calicivirus in infected cells and evidence for its expression from a single, functionally bicistronic, subgenomic mRNA. Journal of General Virology. 77(1). 123–127. 66 indexed citations
20.

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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