Ting Qi

6.4k total citations · 2 hit papers
39 papers, 1.4k citations indexed

About

Ting Qi is a scholar working on Genetics, Molecular Biology and Epidemiology. According to data from OpenAlex, Ting Qi has authored 39 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Genetics, 13 papers in Molecular Biology and 8 papers in Epidemiology. Recurrent topics in Ting Qi's work include Genetic Associations and Epidemiology (9 papers), Influenza Virus Research Studies (8 papers) and Genetic Mapping and Diversity in Plants and Animals (8 papers). Ting Qi is often cited by papers focused on Genetic Associations and Epidemiology (9 papers), Influenza Virus Research Studies (8 papers) and Genetic Mapping and Diversity in Plants and Animals (8 papers). Ting Qi collaborates with scholars based in China, Australia and United States. Ting Qi's co-authors include Jian Yang, Peter M. Visscher, Naomi R. Wray, Zhili Zheng, Yang Wu, Longda Jiang, Kathryn E. Kemper, Zhihong Zhu, Jian Zeng and Futao Zhang and has published in prestigious journals such as Nature Communications, Nature Genetics and PLoS ONE.

In The Last Decade

Ting Qi

37 papers receiving 1.3k citations

Hit Papers

Integrative analysis of omics summary data reveals putati... 2018 2026 2020 2023 2018 2019 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ting Qi China 17 654 519 197 174 109 39 1.4k
Wei Si China 22 229 0.4× 648 1.2× 92 0.5× 112 0.6× 95 0.9× 105 1.5k
Loan Nguyen United States 26 543 0.8× 1.2k 2.3× 177 0.9× 248 1.4× 129 1.2× 79 2.1k
Nathalie Daniel France 22 577 0.9× 893 1.7× 66 0.3× 140 0.8× 159 1.5× 67 1.9k
Doug Speed Denmark 13 1.5k 2.3× 647 1.2× 336 1.7× 125 0.7× 60 0.6× 32 2.2k
Shuyun Li China 18 180 0.3× 275 0.5× 133 0.7× 121 0.7× 140 1.3× 85 929
Carrie J. Finno United States 22 245 0.4× 600 1.2× 60 0.3× 168 1.0× 48 0.4× 122 1.5k
Sarah J. Campbell United Kingdom 12 1.1k 1.7× 549 1.1× 149 0.8× 322 1.9× 296 2.7× 16 2.2k
Chris C. A. Spencer United Kingdom 20 1.3k 2.0× 989 1.9× 174 0.9× 216 1.2× 129 1.2× 26 2.3k
Margarita Salas Argentina 17 381 0.6× 1.1k 2.2× 124 0.6× 134 0.8× 89 0.8× 33 1.8k
David L. Aylor United States 17 383 0.6× 334 0.6× 158 0.8× 53 0.3× 105 1.0× 28 912

Countries citing papers authored by Ting Qi

Since Specialization
Citations

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

Fields of papers citing papers by Ting Qi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ting Qi

This figure shows the co-authorship network connecting the top 25 collaborators of Ting Qi. A scholar is included among the top collaborators of Ting Qi 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 Ting Qi. Ting Qi 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.
Yu, Mengmeng, Zhenyu Zhang, Haili Zhang, et al.. (2024). Avian ANP32A incorporated in avian influenza A virions promotes interspecies transmission by priming early viral replication in mammals. Science Advances. 10(5). eadj4163–eadj4163. 11 indexed citations
2.
Qi, Ting, et al.. (2024). From genetic associations to genes: methods, applications, and challenges. Trends in Genetics. 40(8). 642–667. 19 indexed citations
3.
Qi, Ting, Shihao Zhu, Yunsheng Li, et al.. (2023). Maternal aging increases offspring adult body size via transmission of donut-shaped mitochondria. Cell Research. 33(11). 821–834. 11 indexed citations
4.
Wu, Yang, Ting Qi, Naomi R. Wray, et al.. (2023). Joint analysis of GWAS and multi-omics QTL summary statistics reveals a large fraction of GWAS signals shared with molecular phenotypes. Cell Genomics. 3(8). 100344–100344. 21 indexed citations
5.
Wang, Yan, Guanqin Ma, Xuefeng Wang, et al.. (2022). Keap1 recognizes EIAV early accessory protein Rev to promote antiviral defense. PLoS Pathogens. 18(2). e1009986–e1009986. 9 indexed citations
6.
Qi, Ting, Yang Wu, Hailing Fang, et al.. (2022). Genetic control of RNA splicing and its distinct role in complex trait variation. Nature Genetics. 54(9). 1355–1363. 96 indexed citations
7.
Sun, Xiwei, Angli Xue, Ting Qi, et al.. (2021). Tumor Mutational Burden Is Polygenic and Genetically Associated with Complex Traits and Diseases. Cancer Research. 81(5). 1230–1239. 8 indexed citations
8.
Byrne, Enda M., Zhihong Zhu, Ting Qi, et al.. (2020). Conditional GWAS analysis to identify disorder-specific SNPs for psychiatric disorders. Molecular Psychiatry. 26(6). 2070–2081. 44 indexed citations
9.
Wu, Yang, Ting Qi, Huanwei Wang, et al.. (2020). Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data. Nature Communications. 11(1). 2061–2061. 6 indexed citations
10.
Jiang, Longda, Zhili Zheng, Ting Qi, et al.. (2019). A resource-efficient tool for mixed model association analysis of large-scale data. Nature Genetics. 51(12). 1749–1755. 286 indexed citations breakdown →
11.
Zhang, Futao, Wenhan Chen, Zhihong Zhu, et al.. (2019). OSCA: a tool for omic-data-based complex trait analysis. Genome biology. 20(1). 107–107. 76 indexed citations
12.
Qi, Ting, Yue Hu, Zhe Hu, et al.. (2018). Development of an antigen-capture ELISA for the quantitation of equine arteritis virus in culture supernatant. Archives of Virology. 163(6). 1469–1478. 2 indexed citations
13.
Wu, Yang, Jian Zeng, Futao Zhang, et al.. (2018). Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits. Nature Communications. 9(1). 918–918. 306 indexed citations breakdown →
14.
Zhang, Futao, et al.. (2015). Mixed Linear Model Approaches of Association Mapping for Complex Traits Based on Omics Variants. Scientific Reports. 5(1). 10298–10298. 41 indexed citations
15.
Xu, Haiming, Xiwei Sun, Ting Qi, et al.. (2014). Multivariate Dimensionality Reduction Approaches to Identify Gene-Gene and Gene-Environment Interactions Underlying Multiple Complex Traits. PLoS ONE. 9(9). e108103–e108103. 16 indexed citations
16.
Lu, Gang, Jie Chen, Wei Guo, et al.. (2013). Isolation and characterization of equine influenza viruses (H3N8) from China, 2010-2011.. Pakistan Veterinary Journal. 33(2). 237–239. 2 indexed citations
17.
Zhao, Shihua, et al.. (2013). Identification of a conserved B-cell epitope in the equine arteritis virus (EAV) N protein using the pepscan technique. Virus Genes. 47(2). 292–297. 8 indexed citations
18.
Qi, Ting, Wei Guo, Wen-Qiang Huang, et al.. (2010). Isolation and genetic characterization of H3N8 equine influenza virus from donkeys in China. Veterinary Microbiology. 144(3-4). 455–460. 37 indexed citations
19.
Qi, Ting & Shangjin Cui. (2009). Expression, purification, and characterization of recombinant NS-1, the porcine parvovirus non-structural protein. Journal of Virological Methods. 157(1). 93–97. 2 indexed citations
20.
Qi, Ting & Shangjin Cui. (2009). Expression of porcine parvovirus VP2 gene requires codon optimized E. coli cells. Virus Genes. 39(2). 217–222. 13 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026