Donald Seto

6.2k total citations · 1 hit paper
97 papers, 4.4k citations indexed

About

Donald Seto is a scholar working on Genetics, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Donald Seto has authored 97 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Genetics, 55 papers in Molecular Biology and 46 papers in Infectious Diseases. Recurrent topics in Donald Seto's work include Virus-based gene therapy research (62 papers), Viral gastroenteritis research and epidemiology (41 papers) and Viral Infectious Diseases and Gene Expression in Insects (25 papers). Donald Seto is often cited by papers focused on Virus-based gene therapy research (62 papers), Viral gastroenteritis research and epidemiology (41 papers) and Viral Infectious Diseases and Gene Expression in Insects (25 papers). Donald Seto collaborates with scholars based in United States, China and Canada. Donald Seto's co-authors include James Chodosh, Morris S. Jones, Padmanabhan Mahadevan, David W. Dyer, Greg Wiederrecht, Carl S. Parker, Christopher M. Robinson, Jason Seto, Andrew M. Kropinski and Rob Lavigne and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Donald Seto

95 papers receiving 4.4k citations

Hit Papers

align trajectories

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.

Tracking SARS-CoV-2 Omicron diverse spike gene mutations identifies multiple inter-variant recombination events

2022 137 citations Junxian Ou, Wendong Lan et al. Signal Transduction and Targeted Therapy profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Donald Seto United States	36	2.1k	2.0k	1.8k	1.0k	1.0k	97	4.4k
Michael A. Whitt United States	40	1.6k 0.8×	1.4k 0.7×	2.2k 1.2×	2.5k 2.5×	306 0.3×	80	5.5k
Amiya K. Banerjee United States	45	1.4k 0.7×	1.5k 0.8×	1.5k 0.9×	2.8k 2.7×	658 0.7×	119	5.1k
Roy Duncan Canada	38	1.4k 0.7×	1.1k 0.6×	1.8k 1.0×	487 0.5×	414 0.4×	91	3.5k
Philip J. Kranzusch United States	41	755 0.4×	3.8k 1.9×	1.8k 1.0×	1.0k 1.0×	946 0.9×	69	6.6k
Partho Ghosh United States	37	1.1k 0.5×	2.2k 1.1×	647 0.4×	383 0.4×	542 0.5×	79	4.9k
Trudy G. Morrison United States	41	1.1k 0.5×	1.1k 0.5×	1.1k 0.6×	3.2k 3.2×	436 0.4×	105	4.4k
J K Rose United States	49	1.7k 0.8×	3.0k 1.5×	1.2k 0.7×	2.2k 2.1×	709 0.7×	65	6.5k
Stephen F. Little United States	34	1.3k 0.6×	3.0k 1.5×	904 0.5×	375 0.4×	532 0.5×	72	3.7k
Kimmo Virtaneva United States	31	888 0.4×	1.2k 0.6×	1.3k 0.7×	794 0.8×	200 0.2×	55	4.5k
Ben Peeters Netherlands	39	1.2k 0.6×	894 0.5×	1.1k 0.6×	3.4k 3.3×	236 0.2×	107	4.9k

Countries citing papers authored by Donald Seto

Since Specialization

Citations

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

Fields of papers citing papers by Donald Seto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Donald Seto

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

All Works

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20 of 20 papers shown

Dehghan, Shoaleh, et al.. (2026). Evolution of Human Adenoviruses, a Double-Stranded DNA Viral Pathogen Documented Through Genomics and Bioinformatics and Viewed Through a Web Resource Database. Viruses. 18(2). 251–251.

Li, Yiqiang, Jiangtao Wu, Dingbin Chen, et al.. (2025). High case fatality rate of human adenovirus type 7 infections in children: a meta-analysis and phylogenetic study of HAdV-7 epidemics over the past seven decades. Emerging Microbes & Infections. 14(1). 2582911–2582911.

Chen, Dingbin, Yuqian Yan, Ting Mei, et al.. (2024). Construction and validation of a mouse model for studying severe human adenovirus infections. Virologica Sinica. 39(6). 963–973. 1 indexed citations

Lan, Wendong, Yiqiang Li, Junxian Ou, et al.. (2023). Isolation of novel simian adenoviruses from macaques for development of a vector for human gene therapy and vaccines. Journal of Virology. 97(10). e0101423–e0101423. 5 indexed citations

Zang, Na, Jing Zhang, Yu He, et al.. (2023). Genome and proteomic analysis of risk factors for fatal outcome in children with severe community‐acquired pneumonia caused by human adenovirus 7. Journal of Medical Virology. 95(11). e29182–e29182. 11 indexed citations

Zhao, Shanshan, Yi Ren, Lian Li, et al.. (2023). Generation of Human Embryonic Stem Cell-Derived Lung Organoids for Modeling Infection and Replication Differences between Human Adenovirus Types 3 and 55 and Evaluating Potential Antiviral Drugs. Journal of Virology. 97(5). e0020923–e0020923. 14 indexed citations

Wu, Xiaowei, Jing Zhang, Wendong Lan, et al.. (2022). Molecular Typing and Rapid Identification of Human Adenoviruses Associated With Respiratory Diseases Using Universal PCR and Sequencing Primers for the Three Major Capsid Genes: Penton Base, Hexon, and Fiber. Frontiers in Microbiology. 13. 30 indexed citations

Ou, Junxian, Wendong Lan, Xiaowei Wu, et al.. (2022). Tracking SARS-CoV-2 Omicron diverse spike gene mutations identifies multiple inter-variant recombination events. Signal Transduction and Targeted Therapy. 7(1). 138–138. 137 indexed citations breakdown →

Ou, Junxian, Zhonghua Zhou, Ruixue Dai, et al.. (2021). V367F Mutation in SARS-CoV-2 Spike RBD Emerging during the Early Transmission Phase Enhances Viral Infectivity through Increased Human ACE2 Receptor Binding Affinity. Journal of Virology. 95(16). e0061721–e0061721. 75 indexed citations

10.

Su, Ting, Ashrafali Mohamed Ismail, Meeta Mistry, et al.. (2021). OCT4 and YY1 transcription factors regulate gene expression of an adenoviral ocular pathogen. Investigative Ophthalmology & Visual Science. 62(8). 1954–1954. 1 indexed citations

11.

Yan, Yuqian, Liqiang Feng, Jing Zhang, et al.. (2020). Construction and Characterization of a Novel Recombinant Attenuated and Replication-Deficient Candidate Human Adenovirus Type 3 Vaccine: “Adenovirus Vaccine Within an Adenovirus Vector”. Virologica Sinica. 36(3). 354–364. 12 indexed citations

12.

Dehghan, Shoaleh, Siddharth Sridhar, Susanna K. P. Lau, et al.. (2019). A Survey of Recent Adenoviral Respiratory Pathogens in Hong Kong Reveals Emergent and Recombinant Human Adenovirus Type 4 (HAdV-E4) Circulating in Civilian Populations. Viruses. 11(2). 129–129. 34 indexed citations

13.

Zhang, Qiwei, Shoaleh Dehghan, & Donald Seto. (2016). Pitfalls of restriction enzyme analysis in identifying, characterizing, typing, and naming viral pathogens in the era of whole genome data, as illustrated by HAdV type 55. Virologica Sinica. 31(5). 448–453. 8 indexed citations

14.

Singh, Gurdeep, Xiaohong Zhou, Jeong Yoon Lee, et al.. (2015). Recombination of the epsilon determinant and corneal tropism: Human adenovirus species D types 15, 29, 56, and 69. Virology. 485. 452–459. 24 indexed citations

15.

Adriaenssens, Evelien M., Robert A. Edwards, John J. Nash, et al.. (2014). Integration of genomic and proteomic analyses in the classification of the Siphoviridae family. Virology. 477. 144–154. 48 indexed citations

16.

Dehghan, Shoaleh, Jason Seto, Morris S. Jones, et al.. (2013). Simian adenovirus type 35 has a recombinant genome comprising human and simian adenovirus sequences, which predicts its potential emergence as a human respiratory pathogen. Virology. 447(1-2). 265–273. 22 indexed citations

17.

Mahadevan, Padmanabhan & Donald Seto. (2008). Data Mining Pathogen Genomes Using GeneOrder and CoreGenes: Gene Order, Synteny, and Proteomes.. 234–240. 1 indexed citations

18.

Lin, Baochuan, Zheng Wang, Gary J. Vora, et al.. (2006). Broad-spectrum respiratory tract pathogen identification using resequencing DNA microarrays. Genome Research. 16(4). 527–535. 106 indexed citations

19.

Purkayastha, Anjan, et al.. (2004). Genomic and bioinformatics analysis of HAdV-7, a human adenovirus of species B1 that causes acute respiratory disease: implications for vector development in human gene therapy. Virology. 332(1). 114–129. 21 indexed citations

20.

Seto, Donald, Ben F. Koop, & Leroy Hood. (1993). An Experimentally Derived Data Set Constructed for Testing Large-Scale DNA Sequence Assembly Algorithms. Genomics. 15(3). 673–676. 21 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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