Su Qian

3.2k total citations · 1 hit paper
17 papers, 1.8k citations indexed

About

Su Qian is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Endocrine and Autonomic Systems. According to data from OpenAlex, Su Qian has authored 17 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Cellular and Molecular Neuroscience and 6 papers in Endocrine and Autonomic Systems. Recurrent topics in Su Qian's work include Regulation of Appetite and Obesity (6 papers), Neuropeptides and Animal Physiology (5 papers) and Biochemical Analysis and Sensing Techniques (3 papers). Su Qian is often cited by papers focused on Regulation of Appetite and Obesity (6 papers), Neuropeptides and Animal Physiology (5 papers) and Biochemical Analysis and Sensing Techniques (3 papers). Su Qian collaborates with scholars based in United States, China and France. Su Qian's co-authors include Douglas J. MacNeil, Drew T. Weingarth, Xiao-Ming Guan, Myrna E. Trumbauer, Donald J. Marsh, Easter G. Frazier, Zhu Shen, Lex H.T. Van der Ploeg, Airu Chen and Andrew Howard and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Neuron.

In The Last Decade

Su Qian

17 papers receiving 1.7k citations

Hit Papers

Orexigenic Action of Peripheral Ghrelin Is Mediated by Ne... 2004 2026 2011 2018 2004 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Su Qian United States 13 952 848 577 422 251 17 1.8k
Shirly Pinto United States 16 1.3k 1.4× 939 1.1× 770 1.3× 548 1.3× 295 1.2× 25 2.5k
Dong Kong United States 22 894 0.9× 718 0.8× 400 0.7× 862 2.0× 259 1.0× 29 2.4k
Lawrence M. Maness United States 19 1.3k 1.4× 896 1.1× 905 1.6× 372 0.9× 492 2.0× 21 2.2k
Laura M. Frago Spain 24 648 0.7× 546 0.6× 236 0.4× 500 1.2× 235 0.9× 77 1.9k
Simon Heß Germany 16 640 0.7× 507 0.6× 261 0.5× 650 1.5× 152 0.6× 25 1.7k
Bengt‐Frederik Belgardt Germany 15 871 0.9× 735 0.9× 288 0.5× 976 2.3× 494 2.0× 28 2.4k
Heather Halem United States 16 723 0.8× 829 1.0× 535 0.9× 379 0.9× 223 0.9× 29 1.6k
Oksana Palyha United States 16 1.8k 1.9× 981 1.2× 1.2k 2.1× 509 1.2× 226 0.9× 23 2.5k
Hind Al‐Qassab United Kingdom 11 674 0.7× 701 0.8× 259 0.4× 500 1.2× 162 0.6× 12 1.5k
Derek J. Zimmer United States 19 686 0.7× 459 0.5× 268 0.5× 635 1.5× 179 0.7× 19 1.5k

Countries citing papers authored by Su Qian

Since Specialization
Citations

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

Fields of papers citing papers by Su Qian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Su Qian

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

All Works

17 of 17 papers shown
1.
Qian, Su. (2014). Risk Factors of Advanced Non-small Lung Cancer with Pulmonary Infection. Zhongliu fangzhi yanjiu. 1 indexed citations
2.
Qian, Su, et al.. (2013). Assay development of inducible human renal phosphate transporter Npt2A (SLC34A1) in Flp-In-Trex-HEK293 cells. European Journal of Pharmacology. 721(1-3). 332–340. 1 indexed citations
3.
Tong, Chao, Alex Morrison, Su Qian, et al.. (2012). Impaired SIRT1 nucleocytoplasmic shuttling in the senescent heart during ischemic stress. The FASEB Journal. 27(11). 4332–4342. 103 indexed citations
4.
Wang, Liping, James Hubert, Sang Hyuck Lee, et al.. (2011). Discovery of pyrimidine carboxamides as potent and selective CCK1 receptor agonists. Bioorganic & Medicinal Chemistry Letters. 21(10). 2911–2915. 11 indexed citations
5.
Zhu, Cheng, Thomas J. Bateman, Zhe‐Sheng Chen, et al.. (2008). Discovery of imidazole carboxamides as potent and selective CCK1R agonists. Bioorganic & Medicinal Chemistry Letters. 18(15). 4393–4396. 17 indexed citations
6.
Rao, Yan, Min Lü, Fei Ge, et al.. (2008). Regulation of Synaptic Efficacy in Hypocretin/Orexin-Containing Neurons by Melanin Concentrating Hormone in the Lateral Hypothalamus. Journal of Neuroscience. 28(37). 9101–9110. 100 indexed citations
7.
Qian, Su, et al.. (2008). Deficiency in Cytosolic Malic Enzyme Does Not Increase Acetaminophen‐Induced Hepato‐Toxicity. Basic & Clinical Pharmacology & Toxicology. 103(1). 36–42. 6 indexed citations
8.
Berger, Richard, Cheng Zhu, Zhe‐Sheng Chen, et al.. (2008). 2-Substituted piperazine-derived imidazole carboxamides as potent and selective CCK1R agonists for the treatment of obesity. Bioorganic & Medicinal Chemistry Letters. 18(17). 4833–4837. 26 indexed citations
9.
Ronnebaum, Sarah M., Mette V. Jensen, Hans E. Hohmeier, et al.. (2008). Silencing of Cytosolic or Mitochondrial Isoforms of Malic Enzyme Has No Effect on Glucose-stimulated Insulin Secretion from Rodent Islets. Journal of Biological Chemistry. 283(43). 28909–28917. 63 indexed citations
10.
Gomori, Akira, Akane Ishihara, Makoto Ito, et al.. (2007). Blockade of MCH1 receptor signalling ameliorates obesity and related hepatic steatosis in ovariectomized mice. British Journal of Pharmacology. 151(6). 900–908. 26 indexed citations
11.
Lalonde, Robert & Su Qian. (2007). Exploratory activity, motor coordination, and spatial learning in Mchr1 knockout mice. Behavioural Brain Research. 178(2). 293–304. 23 indexed citations
12.
Chen, Airu, Chunsheng Zhang, John R. Lamb, et al.. (2005). Diet Induction of Monocyte Chemoattractant Protein‐1 and its Impact on Obesity. Obesity Research. 13(8). 1311–1320. 181 indexed citations
13.
Lewis, Huw D., Dirk Beher, David W. Smith, et al.. (2004). Novel aspects of accumulation dynamics and Aβ composition in transgenic models of AD. Neurobiology of Aging. 25(9). 1175–1185. 17 indexed citations
14.
Trumbauer, Myrna E., Drew T. Weingarth, J. R. Adams, et al.. (2004). Orexigenic Action of Peripheral Ghrelin Is Mediated by Neuropeptide Y and Agouti-Related Protein. Endocrinology. 145(6). 2607–2612. 525 indexed citations breakdown →
15.
Qian, Su, Howard Chen, Drew T. Weingarth, et al.. (2002). Neither Agouti-Related Protein nor Neuropeptide Y Is Critically Required for the Regulation of Energy Homeostasis in Mice. Molecular and Cellular Biology. 22(14). 5027–5035. 335 indexed citations
16.
Xia, Xuefeng, Su Qian, Salvador Soriano, et al.. (2001). Loss of presenilin 1 is associated with enhanced β-catenin signaling and skin tumorigenesis. Proceedings of the National Academy of Sciences. 98(19). 10863–10868. 191 indexed citations
17.
Qian, Su, Ping Jiang, Xiao-Ming Guan, et al.. (1998). Mutant Human Presenilin 1 Protects presenilin 1 Null Mouse against Embryonic Lethality and Elevates Aβ1–42/43 Expression. Neuron. 20(3). 611–617. 147 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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