Jing Qian

5.5k total citations · 1 hit paper
92 papers, 3.2k citations indexed

About

Jing Qian is a scholar working on Molecular Biology, Statistics and Probability and Genetics. According to data from OpenAlex, Jing Qian has authored 92 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 14 papers in Statistics and Probability and 13 papers in Genetics. Recurrent topics in Jing Qian's work include Neuroscience and Neuropharmacology Research (11 papers), Statistical Methods and Inference (11 papers) and Statistical Methods and Bayesian Inference (8 papers). Jing Qian is often cited by papers focused on Neuroscience and Neuropharmacology Research (11 papers), Statistical Methods and Inference (11 papers) and Statistical Methods and Bayesian Inference (8 papers). Jing Qian collaborates with scholars based in United States, China and France. Jing Qian's co-authors include Jeffrey L. Noebels, Rebecca A. Betensky, Peter Saggau, Bradley T. Hyman, Alberto Serrano‐Pozo, William F. Colmers, Sarah E. Monsell, James D. Joseph, Gang Shao and Nhin Lu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Oncology.

In The Last Decade

Jing Qian

86 papers receiving 3.1k citations

Hit Papers

A Clinically Relevant Androgen Receptor Mutation Confers ... 2013 2026 2017 2021 2013 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jing Qian United States 29 1.2k 825 598 499 496 92 3.2k
Fumitoshi Satoh Japan 46 1.5k 1.3× 884 1.1× 280 0.5× 330 0.7× 368 0.7× 199 6.7k
Li Liu China 34 1.8k 1.5× 562 0.7× 1.3k 2.2× 589 1.2× 222 0.4× 264 5.4k
Xuefeng Wang China 31 1.1k 1.0× 834 1.0× 303 0.5× 372 0.7× 195 0.4× 168 3.2k
Jeanette Erdmann Germany 44 2.1k 1.8× 531 0.6× 458 0.8× 1.3k 2.6× 265 0.5× 181 5.8k
Vidar M. Steen Norway 39 1.3k 1.1× 349 0.4× 628 1.1× 763 1.5× 167 0.3× 101 4.1k
Na Zhao China 31 1.8k 1.5× 612 0.7× 1.8k 3.1× 243 0.5× 185 0.4× 139 4.9k
Bonnie E. Lonze United States 31 1.6k 1.4× 1.5k 1.8× 577 1.0× 360 0.7× 305 0.6× 96 5.3k
Helen E. Benson United Kingdom 15 2.5k 2.1× 1.2k 1.4× 894 1.5× 220 0.4× 246 0.5× 18 5.3k
L. Creed Pettigrew United States 35 998 0.9× 881 1.1× 673 1.1× 369 0.7× 982 2.0× 84 5.7k
Marie‐Pierre Dubé Canada 39 1.7k 1.5× 469 0.6× 207 0.3× 877 1.8× 314 0.6× 185 5.6k

Countries citing papers authored by Jing Qian

Since Specialization
Citations

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

Fields of papers citing papers by Jing Qian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jing Qian

This figure shows the co-authorship network connecting the top 25 collaborators of Jing Qian. A scholar is included among the top collaborators of Jing Qian 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 Jing Qian. Jing Qian 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.
Xiao, Fei, et al.. (2025). Low-Dose Dexmedetomidine Attenuates the Dose Requirement of Propofol for Suppression of Body Movement in Patients Undergoing Operative Hysteroscopy. Drug Design Development and Therapy. Volume 19. 1185–1193. 1 indexed citations
3.
Wang, Yiru, Jinfeng Liang, Jing Qian, et al.. (2024). Generation, Characterization, and Preclinical Studies of a Novel NKG2A-Targeted Antibody BRY805 for Cancer Immunotherapy. Antibodies. 13(4). 93–93. 1 indexed citations
4.
Zeber, John E., et al.. (2024). Transitions in health insurance among continuously insured patients with schizophrenia. SHILAP Revista de lepidopterología. 10(1). 25–25. 2 indexed citations
5.
Durbin, Shauna, et al.. (2023). A scoping review of empathy recognition in text using natural language processing. Journal of the American Medical Informatics Association. 31(3). 762–775. 1 indexed citations
6.
Qian, Jing, et al.. (2021). Nonparametric estimation of the survival distribution under covariate‐induced dependent truncation. Biometrics. 78(4). 1390–1401. 5 indexed citations
7.
Ma, Yanxia, Jing Qian, Jamal Hill, et al.. (2020). Abstract 1303: PRTN3, RGCC and SLCO4C1 are critical SOX9-regulated genes that control TNBC growth. Cancer Research. 80(16_Supplement). 1303–1303. 1 indexed citations
8.
Qian, Jing, et al.. (2018). A likelihood‐based approach to transcriptome association analysis. Statistics in Medicine. 38(8). 1357–1373. 6 indexed citations
9.
Chiou, Sy Han, Matthew Austin, Jing Qian, & Rebecca A. Betensky. (2018). Transformation model estimation of survival under dependent truncation and independent censoring. Statistical Methods in Medical Research. 28(12). 3785–3798. 16 indexed citations
10.
Chiou, Sy Han, Jing Qian, Elizabeth C. Mormino, & Rebecca A. Betensky. (2018). Permutation tests for general dependent truncation. Computational Statistics & Data Analysis. 128. 308–324. 9 indexed citations
11.
Qian, Jing, et al.. (2018). Accident analysis based on a similarity mechanism safety system model. Journal of Tsinghua University(Science and Technology). 58(11). 1006–1012.
12.
Reeves, Katherine W., Olivia I. Okereke, Jing Qian, et al.. (2017). Depression, Antidepressant Use, and Breast Cancer Risk in Pre- and Postmenopausal Women: A Prospective Cohort Study. Cancer Epidemiology Biomarkers & Prevention. 27(3). 306–314. 17 indexed citations
13.
Reeves, Katherine W., Olivia I. Okereke, Jing Qian, et al.. (2016). Antidepressant use and circulating prolactin levels. Cancer Causes & Control. 27(7). 853–861. 10 indexed citations
14.
Zhang, Yan, Jing Qian, Mingxi Liu, et al.. (2015). A susceptibility locus rs7099208 is associated with non-obstructive azoospermia via reduction in the expression of FAM160B1. Journal of Biomedical Research. 29(6). 491–491. 2 indexed citations
15.
Qian, Jing, et al.. (2015). Projection-Based Reduced-Order Modeling for Spacecraft Thermal Analysis. Journal of Spacecraft and Rockets. 52(3). 978–989. 22 indexed citations
16.
Song, Hongjun, et al.. (2015). Development of Aeroelastic and Aeroservoelastic Reduced Order Models for Active Structural Control. 56th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. 3 indexed citations
17.
Joseph, James D., Nhin Lu, Jing Qian, et al.. (2013). A Clinically Relevant Androgen Receptor Mutation Confers Resistance to Second-Generation Antiandrogens Enzalutamide and ARN-509. Cancer Discovery. 3(9). 1020–1029. 455 indexed citations breakdown →
18.
Qian, Jing, et al.. (2013). Research on Model Information Integration Technology for Smart Distribution Network. 37(12). 3534–3540.
19.
Qian, Jing & Jeffrey L. Noebels. (2003). Topiramate alters excitatory synaptic transmission in mouse hippocampus. Epilepsy Research. 55(3). 225–233. 44 indexed citations
20.
Qian, Jing & Peter Saggau. (1999). Activity‐dependent modulation of K+ currents at presynaptic terminals of mammalian central synapses. The Journal of Physiology. 519(2). 427–437. 20 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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