Wayne Huggins

1.6k total citations
21 papers, 427 citations indexed

About

Wayne Huggins is a scholar working on Molecular Biology, Experimental and Cognitive Psychology and Genetics. According to data from OpenAlex, Wayne Huggins has authored 21 papers receiving a total of 427 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 3 papers in Experimental and Cognitive Psychology and 3 papers in Genetics. Recurrent topics in Wayne Huggins's work include RNA modifications and cancer (7 papers), RNA and protein synthesis mechanisms (7 papers) and Genetic Associations and Epidemiology (3 papers). Wayne Huggins is often cited by papers focused on RNA modifications and cancer (7 papers), RNA and protein synthesis mechanisms (7 papers) and Genetic Associations and Epidemiology (3 papers). Wayne Huggins collaborates with scholars based in United States, United Kingdom and Japan. Wayne Huggins's co-authors include Christine E. Hajdin, Kevin M. Weeks, David H. Mathews, Christopher W. Leonard, Stanislav Bellaousov, Carol M. Hamilton, Erin M. Ramos, Paul Wollenzien, Heather Junkins and Robert M. Bilder and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Molecular Biology.

In The Last Decade

Wayne Huggins

18 papers receiving 420 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wayne Huggins United States 9 294 42 32 30 27 21 427
Donal J Cox Ireland 10 158 0.5× 15 0.4× 53 1.7× 41 1.4× 14 0.5× 18 459
Lauren E. Petty United States 13 168 0.6× 79 1.9× 37 1.2× 42 1.4× 5 0.2× 27 342
Mária Székely United Kingdom 10 220 0.7× 43 1.0× 26 0.8× 55 1.8× 22 0.8× 31 430
Chinmay Shukla United States 4 271 0.9× 57 1.4× 18 0.6× 5 0.2× 14 0.5× 4 430
Ryan Chu Hong Kong 9 112 0.4× 73 1.7× 39 1.2× 34 1.1× 15 0.6× 22 373
Peter Lenárt Czechia 8 95 0.3× 24 0.6× 18 0.6× 17 0.6× 13 0.5× 20 330
Rodrigo Assar Chile 10 182 0.6× 66 1.6× 8 0.3× 40 1.3× 5 0.2× 26 408
Sarah J. Casey United Kingdom 11 86 0.3× 15 0.4× 19 0.6× 23 0.8× 5 0.2× 15 340
Nicole M. Duffy United States 7 159 0.5× 19 0.5× 20 0.6× 46 1.5× 25 0.9× 11 476
Véronique Paradis Canada 8 123 0.4× 48 1.1× 31 1.0× 7 0.2× 51 1.9× 16 322

Countries citing papers authored by Wayne Huggins

Since Specialization
Citations

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

Fields of papers citing papers by Wayne Huggins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wayne Huggins

This figure shows the co-authorship network connecting the top 25 collaborators of Wayne Huggins. A scholar is included among the top collaborators of Wayne Huggins 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 Wayne Huggins. Wayne Huggins 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.
Crosby, Lori E., Allison A. King, Jerlym S. Porter, et al.. (2025). Recommended measurement protocols for sickle cell disease in the PhenX toolkit: psychosocial factors and social determinants of health. PubMed. 2(1). yoaf019–yoaf019.
2.
Buu, Anne, Johannes Thrul, Amanda M. Bunting, et al.. (2025). Enhancing data compatibility in an evolving landscape: Medical cannabis and polysubstance use protocols in the PhenX Toolkit. Drug and Alcohol Dependence. 278. 113001–113001.
3.
Pan, Huaqin, Stephen W. Erickson, Michael Feolo, et al.. (2022). Identifying Datasets for Cross-Study Analysis in dbGaP using PhenX. Scientific Data. 9(1). 532–532. 3 indexed citations
4.
Ropelewski, Alexander J., Megan A. Rizzo, Jason R. Swedlow, et al.. (2022). Standard metadata for 3D microscopy. Scientific Data. 9(1). 449–449. 8 indexed citations
5.
Zhou, Yi‐Hui, Alison A. Motsinger‐Reif, Huaqin Pan, et al.. (2022). Correlation Analysis of Variables From the Atherosclerosis Risk in Communities Study. Frontiers in Pharmacology. 13. 883433–883433. 1 indexed citations
6.
7.
Öngür, Döst, Cameron S. Carter, Raquel E. Gur, et al.. (2019). Common Data Elements for National Institute of Mental Health–Funded Translational Early Psychosis Research. Biological Psychiatry Cognitive Neuroscience and Neuroimaging. 5(1). 10–22. 4 indexed citations
8.
Dixon, Lisa B., Nev Jones, Rachel Loewy, et al.. (2019). Recommendations and Challenges of the Clinical Services Panel of the PhenX Early Psychosis Working Group. Psychiatric Services. 70(6). 514–517. 5 indexed citations
9.
Eckman, James R., Kathryn L. Hassell, Wayne Huggins, et al.. (2017). Standard measures for sickle cell disease research: the PhenX Toolkit sickle cell disease collections. Blood Advances. 1(27). 2703–2711. 21 indexed citations
10.
Barch, Deanna M., Ian H. Gotlib, Robert M. Bilder, et al.. (2016). Common Measures for National Institute of Mental Health Funded Research. Biological Psychiatry. 79(12). e91–e96. 24 indexed citations
11.
Conway, Kevin P., Genevieve C. Vullo, Ashley Kennedy, et al.. (2014). Data compatibility in the addiction sciences: An examination of measure commonality. Drug and Alcohol Dependence. 141. 153–158. 27 indexed citations
12.
McCarty, Catherine A., Wayne Huggins, Allison E. Aiello, et al.. (2014). PhenX RISING: real world implementation and sharing of PhenX measures. BMC Medical Genomics. 7(1). 16–16. 22 indexed citations
13.
Hajdin, Christine E., Stanislav Bellaousov, Wayne Huggins, et al.. (2013). Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots. Proceedings of the National Academy of Sciences. 110(14). 5498–5503. 247 indexed citations
14.
Whitehead, Nedra, Jane Hammond, Michelle A. Williams, et al.. (2012). The PhenX Toolkit pregnancy and birth collections. Annals of Epidemiology. 22(11). 753–758. 2 indexed citations
15.
Pan, Huaqin, K. A. Tryka, Daniel J. Vreeman, et al.. (2012). Using PhenX measures to identify opportunities for cross-study analysis. Human Mutation. 33(5). 849–857. 24 indexed citations
16.
Huggins, Wayne, Sujit K. Ghosh, & Paul Wollenzien. (2009). Hydrogen bonding and packing density are factors most strongly connected to limiting sites of high flexibility in the 16S rRNA in the 30S ribosome. BMC Structural Biology. 9(1). 49–49. 2 indexed citations
17.
18.
Huggins, Wayne, Sujit K. Ghosh, Kavita Nanda, & Paul Wollenzien. (2005). Internucleotide Movements during Formation of 16 S rRNA–rRNA Photocrosslinks and their Connection to the 30 S Subunit Conformational Dynamics. Journal of Molecular Biology. 354(2). 358–374. 9 indexed citations
19.
20.
Noah, James W., et al.. (2003). Conformational Change in the 16S rRNA in the Escherichia coli 70S Ribosome Induced by P/P- and P/E-Site tRNAPhe Binding. Biochemistry. 42(49). 14386–14396. 4 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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