Benjamin B. Sun

14.0k total citations · 2 hit papers
15 papers, 1.4k citations indexed

About

Benjamin B. Sun is a scholar working on Molecular Biology, Genetics and Surgery. According to data from OpenAlex, Benjamin B. Sun has authored 15 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 8 papers in Genetics and 2 papers in Surgery. Recurrent topics in Benjamin B. Sun's work include Genetic Associations and Epidemiology (8 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers) and Bioinformatics and Genomic Networks (3 papers). Benjamin B. Sun is often cited by papers focused on Genetic Associations and Epidemiology (8 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers) and Bioinformatics and Genomic Networks (3 papers). Benjamin B. Sun collaborates with scholars based in United Kingdom, United States and Germany. Benjamin B. Sun's co-authors include Stephen Burgess, James R Staley, Dirk S. Paul, Adam S. Butterworth, Mihir Kamat, Ian O. Ellis, Robin Young, John Danesh, Praveen Surendran and James Blackshaw and has published in prestigious journals such as Nucleic Acids Research, Nature Medicine and Nature Communications.

In The Last Decade

Benjamin B. Sun

14 papers receiving 1.4k citations

Hit Papers

align trajectories sort by overperformance

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.

PhenoScanner: a database of human genotype–phenotype associations

2016 883 citations James R Staley, James Blackshaw et al. Bioinformatics profile →
A fast and efficient colocalization algorithm for identifying shared genetic risk factors across multiple traits

2021 212 citations Christopher N. Foley, James R Staley et al. Nature Communications profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Benjamin B. Sun	689	444	179	172	161	15	1.4k
Jean Morrison	701 1.0×	538 1.2×	188 1.1×	172 1.0×	147 0.9×	12	1.6k
Konstantin Shakhbazov	629 0.9×	367 0.8×	207 1.2×	140 0.8×	119 0.7×	8	1.4k
Wes Spiller	632 0.9×	252 0.6×	179 1.0×	147 0.9×	119 0.7×	14	1.1k
Nigel W. Rayner	594 0.9×	419 0.9×	133 0.7×	127 0.7×	196 1.2×	25	1.0k
Teresa Ferreira	789 1.1×	571 1.3×	194 1.1×	125 0.7×	164 1.0×	69	2.0k
Amy Jayne McKnight	523 0.8×	754 1.7×	151 0.8×	162 0.9×	296 1.8×	124	2.0k
Christopher J. Groves	569 0.8×	459 1.0×	181 1.0×	135 0.8×	302 1.9×	33	1.3k
Maggie C. Y. Ng	724 1.1×	565 1.3×	158 0.9×	179 1.0×	187 1.2×	49	1.6k
Aris Baras	757 1.1×	669 1.5×	278 1.6×	195 1.1×	216 1.3×	46	1.9k
Maiken E. Gabrielsen	524 0.8×	297 0.7×	133 0.7×	125 0.7×	92 0.6×	26	1.1k

Countries citing papers authored by Benjamin B. Sun

Since Specialization

Citations

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

Fields of papers citing papers by Benjamin B. Sun

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benjamin B. Sun. 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 Benjamin B. Sun. The network helps show where Benjamin B. Sun may publish in the future.

Co-authorship network of co-authors of Benjamin B. Sun

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

All Works

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15 of 15 papers shown

Monahan, Jack, Paul G. O’Reilly, Manik Garg, et al.. (2025). The impact of artificial intelligence on biomarker discovery. Emerging Topics in Life Sciences. 8(2). 89–105. 1 indexed citations

Duff, Eugene, Henrik Zetterberg, Amanda Heslegrave, et al.. (2025). Plasma proteomic evidence for increased β-amyloid pathology after SARS-CoV-2 infection. Nature Medicine. 31(3). 797–806. 10 indexed citations

Lam, Max, et al.. (2025). Circulating Blood-Based Proteins in Psychopathology and Cognition. JAMA Psychiatry. 82(5). 481–481. 2 indexed citations

Gadd, Danni A., Robert F. Hillary, Yipeng Cheng, et al.. (2024). Blood protein assessment of leading incident diseases and mortality in the UK Biobank. Nature Aging. 4(7). 939–948. 38 indexed citations

Hillary, Robert F., Danni A. Gadd, Tin-Chi Lin, et al.. (2024). Systematic discovery of gene-environment interactions underlying the human plasma proteome in UK Biobank. Nature Communications. 15(1). 7346–7346. 2 indexed citations

Sun, Benjamin B., Karsten Suhre, & Bradford W. Gibson. (2024). Promises and Challenges of populational Proteomics in Health and Disease. Molecular & Cellular Proteomics. 23(7). 100786–100786. 15 indexed citations

Luo, Hong, Jana Nano, Agnese Petrera, et al.. (2023). Associations of plasma proteomics with type 2 diabetes and related traits: results from the longitudinal KORA S4/F4/FF4 Study. Diabetologia. 66(9). 1655–1668. 17 indexed citations

Meng, Fansen, et al.. (2022). Transcriptomic and Functional Approaches Unveil the Role of tmRNA in Zinc Acetate Mediated Levofloxacin Sensitivity in Helicobacter pylori. Microbiology Spectrum. 10(6). e0115222–e0115222. 5 indexed citations

Foley, Christopher N., James R Staley, Philip G. Breen, et al.. (2021). A fast and efficient colocalization algorithm for identifying shared genetic risk factors across multiple traits. Nature Communications. 12(1). 764–764. 212 indexed citations breakdown →

10.

Wang, Xuning, et al.. (2021). Effect of Temperature on Metronidazole Resistance in Helicobacter pylori. Frontiers in Microbiology. 12. 681911–681911. 9 indexed citations

11.

Stacey, David, Eric B. Fauman, Daniel Ziemek, et al.. (2018). ProGeM: a framework for the prioritization of candidate causal genes at molecular quantitative trait loci. Nucleic Acids Research. 47(1). e3–e3. 57 indexed citations

12.

Burgess, Stephen, Verena Zuber, Elsa Valdés‐Márquez, Benjamin B. Sun, & Jemma C. Hopewell. (2017). Mendelian randomization with fine‐mapped genetic data: Choosing from large numbers of correlated instrumental variables. Genetic Epidemiology. 41(8). 714–725. 98 indexed citations

13.

Staley, James R, James Blackshaw, Mihir Kamat, et al.. (2016). PhenoScanner: a database of human genotype–phenotype associations. Bioinformatics. 32(20). 3207–3209. 883 indexed citations breakdown →

14.

Hussain, Azhar R., et al.. (2015). Conventional protein kinase C isoforms differentially regulate ADP- and thrombin-evoked Ca2+ signalling in human platelets. Cell Calcium. 58(6). 577–588. 9 indexed citations

15.

Sun, Benjamin B., Sue Monteith, & Morris J. Brown. (1991). 5-HT Receptor is Expressed in Human Epicardial 1ACoronary Artery. Clinical Science. 81(s25). 14P–14P.

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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