Feng Geng

3.5k total citations · 1 hit paper
47 papers, 2.4k citations indexed

About

Feng Geng is a scholar working on Molecular Biology, Cancer Research and Surgery. According to data from OpenAlex, Feng Geng has authored 47 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 17 papers in Cancer Research and 12 papers in Surgery. Recurrent topics in Feng Geng's work include Cancer, Lipids, and Metabolism (13 papers), Cholesterol and Lipid Metabolism (10 papers) and Lipid metabolism and biosynthesis (9 papers). Feng Geng is often cited by papers focused on Cancer, Lipids, and Metabolism (13 papers), Cholesterol and Lipid Metabolism (10 papers) and Lipid metabolism and biosynthesis (9 papers). Feng Geng collaborates with scholars based in United States, China and France. Feng Geng's co-authors include Deliang Guo, Xiang Cheng, Chunming Cheng, Arnab Chakravarti, Xiaoning Wu, Robert E. Maleczka, Leo A. Paquette, Xiaokui Mo, Étienne Lefai and Craig Horbinski and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nucleic Acids Research.

In The Last Decade

Feng Geng

42 papers receiving 2.4k citations

Hit Papers

Lipid metabolism reprogramming and its potential targets ... 2018 2026 2020 2023 2018 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Feng Geng United States 19 1.4k 1.2k 304 299 241 47 2.4k
Hai‐long Piao China 26 1.9k 1.3× 862 0.7× 167 0.5× 271 0.9× 87 0.4× 75 2.9k
Raúl V. Durán Spain 20 1.9k 1.3× 1.3k 1.1× 202 0.7× 179 0.6× 73 0.3× 43 2.7k
Jessica Sudderth United States 16 2.0k 1.4× 1.4k 1.2× 277 0.9× 153 0.5× 73 0.3× 20 2.8k
Frank Weinberg United States 19 2.1k 1.5× 1.2k 1.0× 138 0.5× 228 0.8× 88 0.4× 46 3.3k
Abderrahmane Kaidi United Kingdom 11 1.4k 1.0× 738 0.6× 136 0.4× 150 0.5× 66 0.3× 11 2.5k
Daniele Avanzato Italy 15 996 0.7× 338 0.3× 178 0.6× 92 0.3× 132 0.5× 18 1.8k
Eduardo N. Maldonado United States 26 1.5k 1.1× 471 0.4× 145 0.5× 126 0.4× 59 0.2× 55 2.2k
Christopher J. Porter Canada 17 1.7k 1.2× 838 0.7× 128 0.4× 152 0.5× 48 0.2× 30 2.5k
Huamin Wang China 32 2.3k 1.6× 1.2k 1.0× 78 0.3× 189 0.6× 848 3.5× 78 3.6k
Timothy W. Corson United States 29 2.7k 1.9× 687 0.6× 108 0.4× 126 0.4× 233 1.0× 95 4.5k

Countries citing papers authored by Feng Geng

Since Specialization
Citations

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

Fields of papers citing papers by Feng Geng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feng Geng

This figure shows the co-authorship network connecting the top 25 collaborators of Feng Geng. A scholar is included among the top collaborators of Feng Geng 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 Feng Geng. Feng Geng 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.
He, Liqing, Feng Geng, Xinmin Yin, et al.. (2025). Targeting PGM3 abolishes SREBP-1 activation-hexosamine synthesis feedback regulation to effectively suppress brain tumor growth. Science Advances. 11(16). eadq0334–eadq0334. 1 indexed citations
2.
Huang, Chunxia, Linhui Hu, Feng Geng, et al.. (2025). Efficacy and safety of esketamine on major depression, postpartum depression and perioperative depression: a systematic review and meta-analysis. Molecular Psychiatry. 31(1). 545–558.
5.
Geng, Feng, et al.. (2024). Comparative analysis of biofilm characterization of probiotic Escherichia coli. Frontiers in Microbiology. 15. 1365562–1365562. 5 indexed citations
6.
Zhang, Rui, Meixia Pan, Feng Geng, et al.. (2024). STAT3 activation of SCAP-SREBP-1 signaling upregulates fatty acid synthesis to promote tumor growth. Journal of Biological Chemistry. 300(6). 107351–107351. 9 indexed citations
7.
Shen, Qingqing, Qing Zhang, Yunxiao Liu, et al.. (2024). Association of Pain Intensity and Sensitivity with Suicidal Ideation in Adolescents with Depressive Disorder. Psychology Research and Behavior Management. Volume 17. 3121–3131. 2 indexed citations
8.
Geng, Feng, Yaogang Zhong, Étienne Lefai, et al.. (2023). SREBP-1 upregulates lipophagy to maintain cholesterol homeostasis in brain tumor cells. Cell Reports. 42(7). 112790–112790. 25 indexed citations
9.
Wang, Yadi, et al.. (2023). Label-free analysis of biofilm phenotypes by infrared micro- and correlation spectroscopy. Analytical and Bioanalytical Chemistry. 415(17). 3515–3523. 4 indexed citations
10.
Cheng, Chunming, Feng Geng, Yaogang Zhong, et al.. (2022). Ammonia stimulates SCAP/Insig dissociation and SREBP-1 activation to promote lipogenesis and tumour growth. Nature Metabolism. 4(5). 575–588. 90 indexed citations
11.
Li, Na, Feng Geng, Shumei Liang, & Xiao‐Yan Qin. (2022). USP7 inhibits TIMP2 by up-regulating the expression of EZH2 to activate the NF-κB/PD-L1 axis to promote the development of cervical cancer. Cellular Signalling. 96. 110351–110351. 13 indexed citations
12.
Zhang, Dapeng, Zhichun Liu, Song Wang, et al.. (2022). Sleep disorders mediate the link between childhood trauma and depression severity in children and adolescents with depression. Frontiers in Psychiatry. 13. 993284–993284. 8 indexed citations
13.
Cheng, Xiang, Feng Geng, & Deliang Guo. (2020). DGAT1 protects tumor from lipotoxicity, emerging as a promising metabolic target for cancer therapy. Molecular & Cellular Oncology. 7(6). 1805257–1805257. 15 indexed citations
14.
Geng, Feng, Feng Jiang, Jeffrey J. Rakofsky, et al.. (2020). Psychiatric inpatient beds for youths in China: data from a nation-wide survey. BMC Psychiatry. 20(1). 398–398. 6 indexed citations
15.
Wang, Juan, Yulong Zhang, Zhiwei Liu, et al.. (2020). Schizophrenia patients with a metabolically abnormal obese phenotype have milder negative symptoms. BMC Psychiatry. 20(1). 410–410. 10 indexed citations
16.
Wu, Xiaoning, Feng Geng, Xiang Cheng, et al.. (2020). Lipid Droplets Maintain Energy Homeostasis and Glioblastoma Growth via Autophagic Release of Stored Fatty Acids. iScience. 23(10). 101569–101569. 75 indexed citations
17.
Geng, Feng, Mingjun Fan, Juan Li, et al.. (2019). Knockdown of METTL14 inhibits the growth and invasion of cervical cancer. Translational Cancer Research. 8(6). 2307–2315. 16 indexed citations
18.
Geng, Feng, Xiang Cheng, Xiaoning Wu, et al.. (2016). Inhibition of SOAT1 Suppresses Glioblastoma Growth via Blocking SREBP-1–Mediated Lipogenesis. Clinical Cancer Research. 22(21). 5337–5348. 244 indexed citations
19.
Ru, Peng, Peng Hu, Feng Geng, et al.. (2016). Feedback Loop Regulation of SCAP/SREBP-1 by miR-29 Modulates EGFR Signaling-Driven Glioblastoma Growth. Cell Reports. 16(6). 1527–1535. 65 indexed citations
20.
Zhang, Jinli, Yan Fu, Wei Li, et al.. (2009). Natural isoflavones regulate the quadruplex–duplex competition in human telomeric DNA. Nucleic Acids Research. 37(8). 2471–2482. 28 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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