Longda Jiang

3.5k total citations · 2 hit papers
15 papers, 883 citations indexed

About

Longda Jiang is a scholar working on Genetics, Molecular Biology and Pathology and Forensic Medicine. According to data from OpenAlex, Longda Jiang has authored 15 papers receiving a total of 883 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Genetics, 5 papers in Molecular Biology and 4 papers in Pathology and Forensic Medicine. Recurrent topics in Longda Jiang's work include Genetic Associations and Epidemiology (8 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers) and Single-cell and spatial transcriptomics (3 papers). Longda Jiang is often cited by papers focused on Genetic Associations and Epidemiology (8 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers) and Single-cell and spatial transcriptomics (3 papers). Longda Jiang collaborates with scholars based in Australia, China and United States. Longda Jiang's co-authors include Jian Yang, Zhili Zheng, Hailing Fang, Peter M. Visscher, Naomi R. Wray, Ting Qi, Kathryn E. Kemper, Jian Zeng, Angli Xue and Raya Muttarak and has published in prestigious journals such as Nature Communications, Nature Genetics and SHILAP Revista de lepidopterología.

In The Last Decade

Longda Jiang

14 papers receiving 880 citations

Hit Papers

A generalized linear mixed model association tool for bio... 2019 2026 2021 2023 2021 2019 100 200 300
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. A generalized linear mixed model association tool for biobank-scale data
    2021 333 citations Longda Jiang, Zhili Zheng et al. Nature Genetics profile →
  2. A resource-efficient tool for mixed model association analysis of large-scale data
    2019 286 citations Longda Jiang, Zhili Zheng et al. Nature 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
Longda Jiang Australia 9 467 286 96 82 60 15 883
Nana Matoba United States 12 514 1.1× 343 1.2× 89 0.9× 65 0.8× 69 1.1× 19 927
Karoline Kuchenbaecker United Kingdom 12 548 1.2× 234 0.8× 80 0.8× 119 1.5× 88 1.5× 28 962
Urko M. Marigorta Spain 16 506 1.1× 319 1.1× 73 0.8× 61 0.7× 43 0.7× 29 812
Sebastian Schoenherr Austria 4 523 1.1× 290 1.0× 54 0.6× 109 1.3× 61 1.0× 5 902
Rounak Dey United States 8 486 1.0× 279 1.0× 97 1.0× 48 0.6× 56 0.9× 17 822
Priit Palta Estonia 16 438 0.9× 381 1.3× 71 0.7× 98 1.2× 49 0.8× 43 951
Tomaz Berisa United States 5 701 1.5× 378 1.3× 88 0.9× 70 0.9× 97 1.6× 5 1.1k
Kathryn S. Burch United States 10 514 1.1× 309 1.1× 60 0.6× 43 0.5× 66 1.1× 14 826
Malika Freund United States 7 527 1.1× 410 1.4× 61 0.6× 53 0.6× 73 1.2× 10 882
Armin Schoech United States 9 910 1.9× 583 2.0× 72 0.8× 84 1.0× 87 1.4× 9 1.3k

Countries citing papers authored by Longda Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Longda Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Longda Jiang

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

All Works

15 of 15 papers shown
1.
Jiang, Longda, Efthymia Papalexi, Hans‐Hermann Wessels, et al.. (2025). Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens. Nature Cell Biology. 27(3). 505–517. 5 indexed citations
2.
Nakatsuka, Nathan, Drew Adler, Longda Jiang, et al.. (2025). Improving reproducibility of differentially expressed genes in single-cell transcriptomic studies of neurodegenerative diseases through meta-analysis. Nature Communications. 16(1). 7436–7436.
3.
Xue, Angli, Zhihong Zhu, Huanwei Wang, et al.. (2024). Unravelling the complex causal effects of substance use behaviours on common diseases. SHILAP Revista de lepidopterología. 4(1). 43–43. 7 indexed citations
4.
Li, Ang, Shouye Liu, Andrew Bakshi, et al.. (2023). mBAT-combo: A more powerful test to detect gene-trait associations from GWAS data. The American Journal of Human Genetics. 110(1). 30–43. 13 indexed citations
5.
Zeng, Jian, Angli Xue, Longda Jiang, et al.. (2021). Widespread signatures of natural selection across human complex traits and functional genomic categories. Nature Communications. 12(1). 1164–1164. 59 indexed citations
6.
Guo, Jing, Andrew Bakshi, Ying Wang, et al.. (2021). Quantifying genetic heterogeneity between continental populations for human height and body mass index. Scientific Reports. 11(1). 5240–5240. 20 indexed citations
7.
Jiang, Longda, Zhili Zheng, Hailing Fang, & Jian Yang. (2021). A generalized linear mixed model association tool for biobank-scale data. Nature Genetics. 53(11). 1616–1621. 333 indexed citations breakdown →
8.
Xue, Angli, Longda Jiang, Zhihong Zhu, et al.. (2021). Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes. Nature Communications. 12(1). 20211–20211. 35 indexed citations
9.
Fu, Yuanqing, Fengzhe Xu, Longda Jiang, et al.. (2021). Circulating vitamin C concentration and risk of cancers: a Mendelian randomization study. BMC Medicine. 19(1). 171–171. 54 indexed citations
10.
Xue, Angli, Longda Jiang, Zhihong Zhu, et al.. (2021). Publisher Correction: Genome-wide analyses of behavioural traits are subject to bias by misreports and longitudinal changes. Nature Communications. 12(1). 988–988. 1 indexed citations
11.
Jiang, Longda, Zhili Zheng, Hailing Fang, & Jian Yang. (2021). A generalized linear mixed model association tool for biobank-scale data. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations
12.
Xu, Jun, Quan Nguyen, Joanna Crawford, et al.. (2019). Genotype-free demultiplexing of pooled single-cell RNA-seq. Genome biology. 20(1). 290–290. 46 indexed citations
13.
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 →
14.
Ji, Xin, et al.. (2017). A study of HLA‐B*15:02 in 9 different Chinese ethnics: Implications for carbamazepine related SJS/TEN. HLA. 89(4). 225–229. 6 indexed citations
15.
Muttarak, Raya & Longda Jiang. (2016). Vienna Yearbook of Population Research 2015. IIASA PURE (International Institute of Applied Systems Analysis). 16 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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