Zhaotong Lin

602 total citations · 1 hit paper
16 papers, 249 citations indexed

About

Zhaotong Lin is a scholar working on Genetics, Molecular Biology and Rheumatology. According to data from OpenAlex, Zhaotong Lin has authored 16 papers receiving a total of 249 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Genetics, 9 papers in Molecular Biology and 1 paper in Rheumatology. Recurrent topics in Zhaotong Lin's work include Genetic Associations and Epidemiology (15 papers), Genetic and phenotypic traits in livestock (9 papers) and Genetic Mapping and Diversity in Plants and Animals (8 papers). Zhaotong Lin is often cited by papers focused on Genetic Associations and Epidemiology (15 papers), Genetic and phenotypic traits in livestock (9 papers) and Genetic Mapping and Diversity in Plants and Animals (8 papers). Zhaotong Lin collaborates with scholars based in United States and Hong Kong. Zhaotong Lin's co-authors include Wei Pan, Yangqing Deng, Haoran Xue, Xiaotong Shen, Saonli Basu, Fang Lei and Ling Li and has published in prestigious journals such as Nature Communications, Genetics and The American Journal of Human Genetics.

In The Last Decade

Zhaotong Lin

16 papers receiving 248 citations

Hit Papers

Combining the strengths of inverse-variance weighting and... 2021 2026 2022 2024 2021 50 100 150
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.

  1. Combining the strengths of inverse-variance weighting and Egger regression in Mendelian randomization using a mixture of regressions model
    2021 162 citations Zhaotong Lin, Yangqing Deng et al. PLoS Genetics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhaotong Lin United States 7 136 95 35 29 22 16 249
Diptavo Dutta United States 8 153 1.1× 111 1.2× 19 0.5× 21 0.7× 17 0.8× 17 291
Erin Santa United States 4 158 1.2× 67 0.7× 30 0.9× 38 1.3× 33 1.5× 10 279
Rungnapa Ittiwut Thailand 10 83 0.6× 85 0.9× 14 0.4× 17 0.6× 18 0.8× 26 213
Lina Ghaloul‐Gonzalez United States 10 58 0.4× 131 1.4× 28 0.8× 28 1.0× 24 1.1× 29 254
Jiarui Mi China 11 58 0.4× 63 0.7× 25 0.7× 29 1.0× 15 0.7× 20 249
Anastasia L. Wise United States 6 212 1.6× 99 1.0× 18 0.5× 18 0.6× 23 1.0× 8 339
James P. Cook United Kingdom 8 82 0.6× 52 0.5× 30 0.9× 26 0.9× 17 0.8× 12 202
Tine Tesovnik Slovenia 11 112 0.8× 130 1.4× 13 0.4× 33 1.1× 39 1.8× 25 299
Patricia Z. Page United States 5 126 0.9× 80 0.8× 59 1.7× 16 0.6× 8 0.4× 6 314
Sandra Yang United States 8 91 0.7× 85 0.9× 35 1.0× 65 2.2× 6 0.3× 13 245

Countries citing papers authored by Zhaotong Lin

Since Specialization
Citations

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

Fields of papers citing papers by Zhaotong Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhaotong Lin

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

All Works

16 of 16 papers shown
1.
Lei, Fang, Haoran Xue, Zhaotong Lin, & Wei Pan. (2025). Multivariate proteome-wide association study to identify causal proteins for Alzheimer disease. The American Journal of Human Genetics. 112(2). 291–300. 1 indexed citations
2.
Lin, Zhaotong, et al.. (2025). Unbiased causal inference with Mendelian randomization and covariate-adjusted GWAS data. Human Genetics and Genomics Advances. 6(2). 100412–100412. 1 indexed citations
3.
Lin, Zhaotong, et al.. (2024). Collider bias correction for multiple covariates in GWAS using robust multivariable Mendelian randomization. PLoS Genetics. 20(4). e1011246–e1011246. 2 indexed citations
4.
Lin, Zhaotong & Wei Pan. (2024). A robust cis-Mendelian randomization method with application to drug target discovery. Nature Communications. 15(1). 6072–6072. 9 indexed citations
5.
Lin, Zhaotong. (2024). A novel framework with automated horizontal pleiotropy adjustment in mendelian randomization. Human Genetics and Genomics Advances. 5(4). 100339–100339. 2 indexed citations
6.
Lin, Zhaotong, et al.. (2023). Integrating GWAS summary statistics, individual-level genotypic and omic data to enhance the performance for large-scale trait imputation. Human Molecular Genetics. 32(17). 2693–2703. 1 indexed citations
7.
Lin, Zhaotong, et al.. (2023). DeLIVR: a deep learning approach to IV regression for testing nonlinear causal effects in transcriptome-wide association studies. Biostatistics. 25(2). 468–485. 6 indexed citations
8.
Lin, Zhaotong, et al.. (2023). Inference of causal metabolite networks in the presence of invalid instrumental variables with GWAS summary data. Genetic Epidemiology. 47(8). 585–599. 1 indexed citations
9.
Lin, Zhaotong, Haoran Xue, & Wei Pan. (2023). Combining Mendelian randomization and network deconvolution for inference of causal networks with GWAS summary data. PLoS Genetics. 19(5). e1010762–e1010762. 8 indexed citations
10.
Lin, Zhaotong, et al.. (2023). Using GWAS summary data to impute traits for genotyped individuals. Human Genetics and Genomics Advances. 4(3). 100197–100197. 4 indexed citations
11.
Lin, Zhaotong, Haoran Xue, & Wei Pan. (2023). Robust multivariable Mendelian randomization based on constrained maximum likelihood. The American Journal of Human Genetics. 110(4). 592–605. 23 indexed citations
12.
Lin, Zhaotong, et al.. (2022). Estimating SNP heritability in presence of population substructure in biobank-scale datasets. Genetics. 220(4). 4 indexed citations
13.
Lin, Zhaotong, et al.. (2022). Leveraging omics data to boost the power of genome-wide association studies. Human Genetics and Genomics Advances. 3(4). 100144–100144. 3 indexed citations
14.
Lin, Zhaotong, et al.. (2022). A practical problem with Egger regression in Mendelian randomization. PLoS Genetics. 18(5). e1010166–e1010166. 16 indexed citations
15.
Lin, Zhaotong, et al.. (2022). Accounting for nonlinear effects of gene expression identifies additional associated genes in transcriptome-wide association studies. Human Molecular Genetics. 31(14). 2462–2470. 6 indexed citations
16.
Lin, Zhaotong, Yangqing Deng, & Wei Pan. (2021). Combining the strengths of inverse-variance weighting and Egger regression in Mendelian randomization using a mixture of regressions model. PLoS Genetics. 17(11). e1009922–e1009922. 162 indexed citations breakdown →

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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