Michael Worobey

14.9k total citations · 4 hit papers
81 papers, 8.1k citations indexed

About

Michael Worobey is a scholar working on Infectious Diseases, Epidemiology and Molecular Biology. According to data from OpenAlex, Michael Worobey has authored 81 papers receiving a total of 8.1k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Infectious Diseases, 32 papers in Epidemiology and 15 papers in Molecular Biology. Recurrent topics in Michael Worobey's work include HIV Research and Treatment (14 papers), Influenza Virus Research Studies (11 papers) and Animal Virus Infections Studies (11 papers). Michael Worobey is often cited by papers focused on HIV Research and Treatment (14 papers), Influenza Virus Research Studies (11 papers) and Animal Virus Infections Studies (11 papers). Michael Worobey collaborates with scholars based in United States, United Kingdom and Belgium. Michael Worobey's co-authors include Andrew Rambaut, Edward C. Holmes, Guan‐Zhu Han, Joel O. Wertheim, M. Thomas P. Gilbert, Oliver G. Pybus, Dhanasekaran Vijaykrishna, Samir Bhatt, Y. M. Cheung and Gavin J. D. Smith and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Michael Worobey

79 papers receiving 7.9k citations

Hit Papers

Origins and evolutionary genomics of the 2009 swine-origi... 2009 2026 2014 2020 2009 2016 2022 2024 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Worobey United States 41 3.1k 2.8k 2.0k 1.1k 1.1k 81 8.1k
Trevor Bedford United States 38 2.3k 0.8× 3.6k 1.3× 2.1k 1.1× 1.4k 1.3× 513 0.5× 96 7.6k
Marco Salemi United States 46 1.6k 0.5× 2.9k 1.0× 1.8k 0.9× 1.1k 1.0× 877 0.8× 243 8.4k
Tommy Tsan‐Yuk Lam Hong Kong 38 2.6k 0.8× 4.5k 1.6× 2.5k 1.3× 1.7k 1.5× 1.2k 1.1× 108 10.4k
Nathan Wolfe United States 45 2.1k 0.7× 3.4k 1.2× 1.4k 0.7× 1.1k 1.0× 1.5k 1.4× 117 8.8k
Donald B. Smith United Kingdom 42 3.5k 1.2× 3.3k 1.2× 5.2k 2.6× 1.2k 1.1× 719 0.7× 117 14.6k
Gustavo Palacios United States 52 2.5k 0.8× 5.7k 2.0× 1.9k 1.0× 889 0.8× 436 0.4× 259 10.1k
James O. Lloyd‐Smith United States 45 2.4k 0.8× 3.3k 1.2× 1.2k 0.6× 1.6k 1.4× 1.4k 1.3× 117 9.4k
John Ellis Australia 62 2.5k 0.8× 5.1k 1.8× 1.6k 0.8× 1.7k 1.5× 951 0.9× 365 13.8k
Bryan T. Eaton Australia 42 3.3k 1.1× 5.0k 1.8× 1.2k 0.6× 745 0.7× 1.2k 1.1× 110 7.6k
Ben Murrell United States 32 1.3k 0.4× 2.9k 1.0× 2.5k 1.2× 1.7k 1.5× 403 0.4× 85 9.1k

Countries citing papers authored by Michael Worobey

Since Specialization
Citations

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

Fields of papers citing papers by Michael Worobey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Worobey

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Worobey. A scholar is included among the top collaborators of Michael Worobey 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 Michael Worobey. Michael Worobey 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.
Pekar, Jonathan E., Niema Moshiri, Philippe Lemey, et al.. (2025). Recently reported SARS-CoV-2 genomes suggested to be intermediate between the two early main lineages are instead likely derived. Virus Evolution. 11(1). veaf008–veaf008. 2 indexed citations
2.
Peacock, Thomas P., Louise H. Moncla, Gytis Dudas, et al.. (2024). The global H5N1 influenza panzootic in mammals. Nature. 637(8045). 304–313. 123 indexed citations breakdown →
3.
Larsen, Brendan B., Simona Kraberger, Nathan S. Upham, et al.. (2023). Diverse DNA virus genomes identified in fecal samples of Mexican free-tailed bats (Tadarida brasiliensis) captured in Chiricahua Mountains of southeast Arizona (USA). Virology. 580. 98–111. 7 indexed citations
4.
Montoya, Vincent, Rachel L. Miller, Gideon Mordecai, et al.. (2022). Genomic epidemiology of the first two waves of SARS-CoV-2 in Canada. eLife. 11. 12 indexed citations
5.
Pekar, Jonathan E., Michael Worobey, Niema Moshiri, Konrad Scheffler, & Joel O. Wertheim. (2021). Timing the SARS-CoV-2 index case in Hubei province. Science. 372(6540). 412–417. 105 indexed citations
6.
Worobey, Michael, Jonathan E. Pekar, Brendan B. Larsen, et al.. (2020). The emergence of SARS-CoV-2 in Europe and North America. Science. 370(6516). 564–570. 214 indexed citations
7.
Lemey, Philippe, Samuel L. Hong, Verity Hill, et al.. (2020). Accommodating individual travel history and unsampled diversity in Bayesian phylogeographic inference of SARS-CoV-2. Nature Communications. 11(1). 5110–5110. 85 indexed citations
8.
Suchard, Marc A., Xiang Ji, Sophie Gryseels, et al.. (2019). Divergence dating using mixed effects clock modelling: An application to HIV-1. Virus Evolution. 5(2). vez036–vez036. 16 indexed citations
9.
Gostic, Katelyn M., et al.. (2019). Childhood immune imprinting to influenza A shapes birth year-specific risk during seasonal H1N1 and H3N2 epidemics. PLoS Pathogens. 15(12). e1008109–e1008109. 83 indexed citations
10.
Gostic, Katelyn M., Monique Ambrose, Michael Worobey, & James O. Lloyd‐Smith. (2016). Potent protection against H5N1 and H7N9 influenza via childhood hemagglutinin imprinting. Science. 354(6313). 722–726. 314 indexed citations breakdown →
11.
Worobey, Michael, Thomas D. Watts, Marc A. Suchard, et al.. (2016). 1970s and ‘Patient 0’ HIV-1 genomes illuminate early HIV/AIDS history in North America. Nature. 539(7627). 98–101. 111 indexed citations
12.
13.
Ochman, Howard, Michael Worobey, Chih‐Horng Kuo, et al.. (2010). Evolutionary Relationships of Wild Hominids Recapitulated by Gut Microbial Communities. PLoS Biology. 8(11). e1000546–e1000546. 373 indexed citations
14.
Smith, Gavin J. D., Dhanasekaran Vijaykrishna, Justin Bahl, et al.. (2009). Origins and evolutionary genomics of the 2009 swine-origin H1N1 influenza A epidemic. Nature. 459(7250). 1122–1125. 1663 indexed citations breakdown →
15.
Adam, Rodney D., et al.. (2007). Population Genetics Provides Evidence for Recombination in Giardia. Current Biology. 17(22). 1984–1988. 130 indexed citations
16.
Gilbert, M. Thomas P., Tamara S. Haselkorn, Michael Bunce, et al.. (2007). The Isolation of Nucleic Acids from Fixed, Paraffin-Embedded Tissues–Which Methods Are Useful When?. PLoS ONE. 2(6). e537–e537. 305 indexed citations
17.
Lemey, Philippe, Oliver G. Pybus, Andrew Rambaut, et al.. (2004). The Molecular Population Genetics of HIV-1 Group O. Genetics. 167(3). 1059–1068. 87 indexed citations
18.
Rij, Ronald P. van, et al.. (2003). Evolution of R5 and X4 human immunodeficiency virus type 1 gag sequences in vivo: evidence for recombination. Virology. 314(1). 451–459. 22 indexed citations
19.
Worobey, Michael, et al.. (2001). Evidence for the Non-quasispecies Evolution of RNA Viruses. Molecular Biology and Evolution. 18(6). 987–994. 44 indexed citations
20.
Worobey, Michael & Edward C. Holmes. (2001). Homologous Recombination in GB Virus C/Hepatitis G Virus. Molecular Biology and Evolution. 18(2). 254–261. 58 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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