Timothy C. Yu

482 total citations · 1 hit paper
8 papers, 186 citations indexed

About

Timothy C. Yu is a scholar working on Infectious Diseases, Molecular Biology and Epidemiology. According to data from OpenAlex, Timothy C. Yu has authored 8 papers receiving a total of 186 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Infectious Diseases, 4 papers in Molecular Biology and 3 papers in Epidemiology. Recurrent topics in Timothy C. Yu's work include vaccines and immunoinformatics approaches (2 papers), HIV Research and Treatment (2 papers) and Respiratory viral infections research (2 papers). Timothy C. Yu is often cited by papers focused on vaccines and immunoinformatics approaches (2 papers), HIV Research and Treatment (2 papers) and Respiratory viral infections research (2 papers). Timothy C. Yu collaborates with scholars based in United States, South Africa and Belgium. Timothy C. Yu's co-authors include Jesse D. Bloom, Caelan E. Radford, William W. Hannon, Katharine H. D. Crawford, Bernadeta Dadonaite, Helen Y. Chu, Ariana Ghez Farrell, Raiees Andrabi, Dennis R. Burton and Richard A. Neher and has published in prestigious journals such as Cell, Nature Communications and Journal of Virology.

In The Last Decade

Timothy C. Yu

8 papers receiving 186 citations

Hit Papers

A pseudovirus system enables deep mutational scanning of ... 2023 2026 2024 2025 2023 25 50 75

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Timothy C. Yu United States 6 91 89 38 29 21 8 186
Caelan E. Radford United States 6 113 1.2× 81 0.9× 32 0.8× 24 0.8× 26 1.2× 10 201
Elias Harkins United States 5 77 0.8× 102 1.1× 41 1.1× 23 0.8× 14 0.7× 6 217
Gilles Augusto United Kingdom 7 71 0.8× 133 1.5× 29 0.8× 15 0.5× 11 0.5× 12 224
Carolin Zitzmann United States 8 43 0.5× 146 1.6× 50 1.3× 15 0.5× 24 1.1× 12 254
Fabrice Gallais France 8 74 0.8× 233 2.6× 37 1.0× 24 0.8× 15 0.7× 10 289
Wilhelm Furnon United Kingdom 6 59 0.6× 162 1.8× 23 0.6× 10 0.3× 12 0.6× 9 200
Kevin M. Tuffy United States 7 73 0.8× 52 0.6× 89 2.3× 11 0.4× 14 0.7× 12 181
Hasan Ahmed United States 7 41 0.5× 97 1.1× 50 1.3× 13 0.4× 15 0.7× 17 185
Wenxu Jia China 5 84 0.9× 207 2.3× 23 0.6× 42 1.4× 31 1.5× 6 281
Zikun Yang United States 4 168 1.8× 73 0.8× 29 0.8× 53 1.8× 28 1.3× 9 222

Countries citing papers authored by Timothy C. Yu

Since Specialization
Citations

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

Fields of papers citing papers by Timothy C. Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Timothy C. Yu. 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 Timothy C. Yu. The network helps show where Timothy C. Yu may publish in the future.

Co-authorship network of co-authors of Timothy C. Yu

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

All Works

8 of 8 papers shown
1.
Simonich, Cassandra A., Xiaohui Ju, Timothy C. Yu, et al.. (2025). RSV F evolution escapes some monoclonal antibodies but does not strongly erode neutralization by human polyclonal sera. Journal of Virology. 99(7). e0053125–e0053125. 1 indexed citations
2.
Yu, Timothy C., et al.. (2025). Pleiotropic mutational effects on function and stability constrain the antigenic evolution of influenza haemagglutinin. Nature Ecology & Evolution. 10(3). 452–466. 1 indexed citations
3.
Eguia, Rachel, Juhye Lee, Hugh K. Haddox, et al.. (2024). Age-dependent heterogeneity in the antigenic effects of mutations to influenza hemagglutinin. Cell Host & Microbe. 32(8). 1397–1411.e11. 15 indexed citations
4.
Radford, Caelan E., Philipp Schommers, Lutz Gieselmann, et al.. (2023). Mapping the neutralizing specificity of human anti-HIV serum by deep mutational scanning. Cell Host & Microbe. 31(7). 1200–1215.e9. 17 indexed citations
5.
Dadonaite, Bernadeta, Katharine H. D. Crawford, Caelan E. Radford, et al.. (2023). A pseudovirus system enables deep mutational scanning of the full SARS-CoV-2 spike. Cell. 186(6). 1263–1278.e20. 85 indexed citations breakdown →
6.
Yu, Timothy C., William W. Hannon, William S. DeWitt, et al.. (2022). A biophysical model of viral escape from polyclonal antibodies. Virus Evolution. 8(2). veac110–veac110. 19 indexed citations
7.
Das, Jishnu, Jonathan K. Fallon, Timothy C. Yu, et al.. (2021). Delayed fractional dosing with RTS,S/AS01 improves humoral immunity to malaria via a balance of polyfunctional NANP6- and Pf16-specific antibodies. Med. 2(11). 1269–1286.e9. 19 indexed citations
8.
Yu, Timothy C., Jessica E. Davis, Tal Einav, et al.. (2021). Multiplexed characterization of rationally designed promoter architectures deconstructs combinatorial logic for IPTG-inducible systems. Nature Communications. 12(1). 325–325. 29 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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