De‐Yong Liang

2.2k total citations
46 papers, 1.8k citations indexed

About

De‐Yong Liang is a scholar working on Physiology, Cellular and Molecular Neuroscience and Molecular Biology. According to data from OpenAlex, De‐Yong Liang has authored 46 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Physiology, 20 papers in Cellular and Molecular Neuroscience and 11 papers in Molecular Biology. Recurrent topics in De‐Yong Liang's work include Pain Mechanisms and Treatments (33 papers), Neuropeptides and Animal Physiology (17 papers) and Pediatric Pain Management Techniques (5 papers). De‐Yong Liang is often cited by papers focused on Pain Mechanisms and Treatments (33 papers), Neuropeptides and Animal Physiology (17 papers) and Pediatric Pain Management Techniques (5 papers). De‐Yong Liang collaborates with scholars based in United States, China and Canada. De‐Yong Liang's co-authors include J. David Clark, Xiaoyou Shi, Peyman Sahbaie, Xiangqi Li, Wen‐Wu Li, Gary Peltz, Xiangqi Li, Yuan Sun, Yuan Sun and David C. Yeomans and has published in prestigious journals such as PLoS ONE, Scientific Reports and Pain.

In The Last Decade

De‐Yong Liang

46 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
De‐Yong Liang United States 29 973 556 487 287 252 46 1.8k
Xiangqi Li United States 25 854 0.9× 361 0.6× 478 1.0× 316 1.1× 196 0.8× 49 1.6k
Xiaoyou Shi United States 31 1.2k 1.3× 579 1.0× 501 1.0× 503 1.8× 258 1.0× 54 2.3k
Julie Wieseler‐Frank United States 16 1.3k 1.4× 782 1.4× 372 0.8× 127 0.4× 131 0.5× 19 2.0k
Yul Huh United States 11 1.0k 1.1× 409 0.7× 318 0.7× 141 0.5× 138 0.5× 11 1.9k
Alexander Chamessian United States 12 884 0.9× 491 0.9× 398 0.8× 113 0.4× 108 0.4× 18 1.5k
Chung‐Ren Lin Taiwan 22 505 0.5× 361 0.6× 496 1.0× 190 0.7× 239 0.9× 58 1.8k
Nada Lawand United States 18 1.1k 1.1× 528 0.9× 340 0.7× 129 0.4× 235 0.9× 29 1.7k
Alexander Brack Germany 30 1.2k 1.2× 1.0k 1.8× 527 1.1× 130 0.5× 234 0.9× 59 2.5k
Gudarz Davar United States 21 1.3k 1.3× 683 1.2× 416 0.9× 349 1.2× 144 0.6× 33 2.2k
Jong Yeon Park South Korea 12 1.3k 1.4× 728 1.3× 387 0.8× 80 0.3× 219 0.9× 45 2.2k

Countries citing papers authored by De‐Yong Liang

Since Specialization
Citations

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

Fields of papers citing papers by De‐Yong Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by De‐Yong Liang. 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 De‐Yong Liang. The network helps show where De‐Yong Liang may publish in the future.

Co-authorship network of co-authors of De‐Yong Liang

This figure shows the co-authorship network connecting the top 25 collaborators of De‐Yong Liang. A scholar is included among the top collaborators of De‐Yong Liang 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 De‐Yong Liang. De‐Yong Liang 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.
Griffiths, Brian B., Peyman Sahbaie, Anand N. Rao, et al.. (2019). Pre-treatment with microRNA-181a Antagomir Prevents Loss of Parvalbumin Expression and Preserves Novel Object Recognition Following Mild Traumatic Brain Injury. NeuroMolecular Medicine. 21(2). 170–181. 15 indexed citations
2.
Sahbaie, Peyman, Karen‐Amanda Irvine, De‐Yong Liang, Xiaoyou Shi, & J. David Clark. (2019). Mild Traumatic Brain Injury Causes Nociceptive Sensitization through Spinal Chemokine Upregulation. Scientific Reports. 9(1). 19500–19500. 29 indexed citations
3.
Ma, Xiaojun, et al.. (2018). Treatment of hematomas after anterior cervical spine surgery: A retrospective study of 15 cases. Neurochirurgie. 64(3). 166–170. 11 indexed citations
4.
Sahbaie, Peyman, De‐Yong Liang, Xiaoyou Shi, Yuan Sun, & J. David Clark. (2016). Epigenetic regulation of spinal cord gene expression contributes to enhanced postoperative pain and analgesic tolerance subsequent to continuous opioid exposure. Molecular Pain. 12. 35 indexed citations
5.
Sahbaie, Peyman, Yuan Sun, De‐Yong Liang, Xiaoyou Shi, & J. David Clark. (2014). Curcumin Treatment Attenuates Pain and Enhances Functional Recovery after Incision. Anesthesia & Analgesia. 118(6). 1336–1344. 49 indexed citations
6.
Liang, De‐Yong, Ming Zheng, Yuan Sun, et al.. (2014). The Netrin-1 receptor DCC is a regulator of maladaptive responses to chronic morphine administration. BMC Genomics. 15(1). 345–345. 17 indexed citations
7.
Sun, Yuan, De‐Yong Liang, Peyman Sahbaie, & J. David Clark. (2013). Effects of Methyl Donor Diets on Incisional Pain in Mice. PLoS ONE. 8(10). e77881–e77881. 8 indexed citations
8.
Han, Yaxin, et al.. (2012). Comparative analysis of the influence of Fructus Ligustri Lucidi on a rat lumbar disc herniation model. Molecular Medicine Reports. 12(1). 1225–1232. 4 indexed citations
9.
Liang, De‐Yong, et al.. (2012). Serotonin transporter gene promoter region polymorphisms and serotonin transporter expression in the colonic mucosa of irritable bowel syndrome patients. Neurogastroenterology & Motility. 24(6). 560–560. 32 indexed citations
10.
Liang, De‐Yong, Xiangqi Li, Xiaoyu Shi, et al.. (2011). The complement component C5a receptor mediates pain and inflammation in a postsurgical pain model. Pain. 153(2). 366–372. 41 indexed citations
11.
Jang, Jun Ho, De‐Yong Liang, Kanta Kido, et al.. (2011). Increased local concentration of complement C5a contributes to incisional pain in mice. Journal of Neuroinflammation. 8(1). 80–80. 43 indexed citations
12.
Liang, De‐Yong, Xiaoyou Shi, Xiangqi Li, Jun Li, & J. David Clark. (2007). The β2 adrenergic receptor regulates morphine tolerance and physical dependence. Behavioural Brain Research. 181(1). 118–126. 42 indexed citations
13.
Liang, De‐Yong, et al.. (2006). Chronic pain and genetic background interact and influence opioid analgesia, tolerance, and physical dependence. Pain. 121(3). 232–240. 56 indexed citations
14.
Liang, De‐Yong, et al.. (2006). Genetic variants of the P-glycoprotein gene Abcb1b modulate opioid-induced hyperalgesia, tolerance and dependence. Pharmacogenetics and Genomics. 16(11). 825–835. 52 indexed citations
15.
Li, Xiangqi, et al.. (2005). Spinal CK2 regulates nociceptive signaling in models of inflammatory pain. Pain. 115(1). 182–190. 25 indexed citations
16.
Li, Xiangqi, et al.. (2004). Alterations in spinal cord gene expression after hindpaw formalin injection. Journal of Neuroscience Research. 78(4). 533–541. 22 indexed citations
17.
Liang, De‐Yong, Xiangqi Li, & J. David Clark. (2004). Formalin-induced spinal cord calcium/calmodulin-dependent protein kinase IIα expression is modulated by heme oxygenase in mice. Neuroscience Letters. 360(1-2). 61–64. 24 indexed citations
18.
Liang, De‐Yong & J. David Clark. (2004). Modulation of the NO/CO-cGMP signaling cascade during chronic morphine exposure in mice. Neuroscience Letters. 365(1). 73–77. 34 indexed citations
19.
Liang, De‐Yong, et al.. (2003). Increased expression of Ca2+/calmodulin-dependent protein kinase IIα during chronic morphine exposure. Neuroscience. 123(3). 769–775. 50 indexed citations
20.
Liang, De‐Yong, et al.. (2003). Heme oxygenase type 2 modulates behavioral and molecular changes during chronic exposure to morphine. Neuroscience. 121(4). 999–1005. 44 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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