Lu Qi

4.0k total citations · 1 hit paper
10 papers, 759 citations indexed

About

Lu Qi is a scholar working on Physiology, Pharmacology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Lu Qi has authored 10 papers receiving a total of 759 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Physiology, 3 papers in Pharmacology and 3 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Lu Qi's work include Diet and metabolism studies (4 papers), Obesity, Physical Activity, Diet (3 papers) and Diet, Metabolism, and Disease (3 papers). Lu Qi is often cited by papers focused on Diet and metabolism studies (4 papers), Obesity, Physical Activity, Diet (3 papers) and Diet, Metabolism, and Disease (3 papers). Lu Qi collaborates with scholars based in United States, China and Singapore. Lu Qi's co-authors include Qibin Qi, Eric B. Rimm, Majken K. Jensen, David J. Hunter, Frank B. Hu, Louis R. Pasquale, Walter C. Willett, Frank M. Sacks, Audrey Y. Chu and Paul M. Ridker and has published in prestigious journals such as New England Journal of Medicine, Circulation and Diabetes Care.

In The Last Decade

Lu Qi

10 papers receiving 743 citations

Hit Papers

Sugar-Sweetened Beverages and Genetic Risk of Obesity 2012 2026 2016 2021 2012 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
Lu Qi United States 7 301 299 293 134 126 10 759
Azita Zadeh–Vakili Iran 19 138 0.5× 101 0.3× 333 1.1× 276 2.1× 156 1.2× 58 1.0k
Amel Lamri Canada 14 180 0.6× 129 0.4× 173 0.6× 87 0.6× 143 1.1× 23 610
R L Phillips United States 10 262 0.9× 133 0.4× 391 1.3× 176 1.3× 70 0.6× 10 939
Eun-Gyong Yoo South Korea 13 151 0.5× 62 0.2× 203 0.7× 173 1.3× 87 0.7× 37 733
Shafqat Ahmad United States 13 111 0.4× 102 0.3× 138 0.5× 58 0.4× 47 0.4× 22 375
Mahmoud Ali Kaykhaei Iran 15 100 0.3× 58 0.2× 96 0.3× 166 1.2× 108 0.9× 38 610
Stella Aslibekyan United States 15 135 0.4× 133 0.4× 79 0.3× 85 0.6× 211 1.7× 32 609
Micheline C. Chu United States 14 85 0.3× 116 0.4× 392 1.3× 219 1.6× 190 1.5× 21 1.3k
U Gaspard Belgium 18 51 0.2× 147 0.5× 341 1.2× 344 2.6× 78 0.6× 60 1.0k

Countries citing papers authored by Lu Qi

Since Specialization
Citations

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

Fields of papers citing papers by Lu Qi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lu Qi

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

All Works

10 of 10 papers shown
1.
Hara, Konan, JoAnn E. Manson, Eric B. Rimm, et al.. (2025). Machine-learning approaches to predict individualized treatment effect using a randomized controlled trial. European Journal of Epidemiology. 40(2). 151–166. 2 indexed citations
2.
Liu, Yunfeng, Lu Qi, Minghui Xu, et al.. (2024). Anti-Agrobacterium tumefactions sesquiterpene derivatives from the marine-derived fungus Trichoderma effusum. Frontiers in Microbiology. 15. 1446283–1446283. 3 indexed citations
3.
Zhang, Yahui, et al.. (2022). Talasteroid, a new withanolide from the marine-derived fungus Talaromyces stollii. Natural Product Research. 37(19). 3283–3289. 5 indexed citations
4.
Heianza, Yoriko, Dianjianyi Sun, Steven R. Smith, et al.. (2018). Changes in Gut Microbiota–Related Metabolites and Long-term Successful Weight Loss in Response to Weight-Loss Diets: The POUNDS Lost Trial. Diabetes Care. 41(3). 413–419. 65 indexed citations
5.
Wang, Tiange, Tao Huang, Jae H. Kang, et al.. (2017). Habitual coffee consumption and genetic predisposition to obesity: gene-diet interaction analyses in three US prospective studies. BMC Medicine. 15(1). 97–97. 45 indexed citations
6.
Heianza, Yoriko, Dianjianyi Sun, Tiange Wang, et al.. (2017). Starch Digestion–Related Amylase Genetic Variant Affects 2-Year Changes in Adiposity in Response to Weight-Loss Diets: The POUNDS Lost Trial. Diabetes. 66(9). 2416–2423. 24 indexed citations
7.
Wang, Tiange, Tao Huang, Yoriko Heianza, et al.. (2017). Genetic Susceptibility, Change in Physical Activity, and Long-term Weight Gain. Diabetes. 66(10). 2704–2712. 13 indexed citations
8.
Qi, Qibin, Audrey Y. Chu, Jae‐Heon Kang, et al.. (2012). Sugar-Sweetened Beverages and Genetic Risk of Obesity. New England Journal of Medicine. 367(15). 1387–1396. 380 indexed citations breakdown →
9.
Qi, Qibin, George A. Bray, Steven R. Smith, et al.. (2011). Insulin Receptor Substrate 1 Gene Variation Modifies Insulin Resistance Response to Weight-Loss Diets in a 2-Year Randomized Trial. Circulation. 124(5). 563–571. 103 indexed citations
10.
Qi, Lu, Marilyn C. Cornelis, Peter Kraft, et al.. (2010). Genetic variants in ABO blood group region, plasma soluble E-selectin levels and risk of type 2 diabetes. Human Molecular Genetics. 19(9). 1856–1862. 119 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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