Bingkun K. Chen

421 total citations
14 papers, 317 citations indexed

About

Bingkun K. Chen is a scholar working on Cellular and Molecular Neuroscience, Pathology and Forensic Medicine and Surgery. According to data from OpenAlex, Bingkun K. Chen has authored 14 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cellular and Molecular Neuroscience, 10 papers in Pathology and Forensic Medicine and 7 papers in Surgery. Recurrent topics in Bingkun K. Chen's work include Nerve injury and regeneration (11 papers), Spinal Cord Injury Research (10 papers) and Neurogenesis and neuroplasticity mechanisms (5 papers). Bingkun K. Chen is often cited by papers focused on Nerve injury and regeneration (11 papers), Spinal Cord Injury Research (10 papers) and Neurogenesis and neuroplasticity mechanisms (5 papers). Bingkun K. Chen collaborates with scholars based in United States, Ireland and Austria. Bingkun K. Chen's co-authors include Anthony J. Windebank, Michael J. Yaszemski, Nicolas N. Madigan, Andrew M. Knight, Mahrokh Dadsetan, Siobhán S. McMahon, Jarred J. Nesbitt, Ann M. Schmeichel, Peter J. Grahn and Gemma E. Rooney and has published in prestigious journals such as Biomaterials, International Journal of Molecular Sciences and Transfusion.

In The Last Decade

Bingkun K. Chen

14 papers receiving 309 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bingkun K. Chen United States	10	204	152	102	67	62	14	317
Magdalini Tsintou United Kingdom	7	192 0.9×	104 0.7×	91 0.9×	75 1.1×	67 1.1×	8	315
Kyriakos Dalamagkas United Kingdom	8	193 0.9×	106 0.7×	91 0.9×	74 1.1×	67 1.1×	8	333
Jarred J. Nesbitt United States	6	219 1.1×	128 0.8×	100 1.0×	67 1.0×	55 0.9×	13	326
Julien Bouyer United States	8	210 1.0×	140 0.9×	75 0.7×	57 0.9×	51 0.8×	13	326
Vanessa M. Doulames United States	9	152 0.7×	107 0.7×	70 0.7×	56 0.8×	58 0.9×	12	366
Yudan Gao China	12	162 0.8×	81 0.5×	67 0.7×	54 0.8×	63 1.0×	22	319
I. Cortés Maldonado Netherlands	8	125 0.6×	114 0.8×	79 0.8×	61 0.9×	52 0.8×	10	297
Shayan Abdollah Zadegan Iran	13	158 0.8×	242 1.6×	176 1.7×	38 0.6×	59 1.0×	36	450
Ahad M. Siddiqui United States	11	164 0.8×	214 1.4×	105 1.0×	30 0.4×	37 0.6×	17	375
Irma Vismara Italy	6	175 0.9×	180 1.2×	67 0.7×	76 1.1×	52 0.8×	6	398

Countries citing papers authored by Bingkun K. Chen

Since Specialization

Citations

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

Fields of papers citing papers by Bingkun K. Chen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bingkun K. Chen. 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 Bingkun K. Chen. The network helps show where Bingkun K. Chen may publish in the future.

Co-authorship network of co-authors of Bingkun K. Chen

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

All Works

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14 of 14 papers shown

1.

Siddiqui, Ahad M., Bingkun K. Chen, Jarred J. Nesbitt, et al.. (2023). Open-Spaced Ridged Hydrogel Scaffolds Containing TiO2-Self-Assembled Monolayer of Phosphonates Promote Regeneration and Recovery Following Spinal Cord Injury. International Journal of Molecular Sciences. 24(12). 10250–10250. 5 indexed citations

2.

Siddiqui, Ahad M., Bruce E. Knudsen, Shuya Zhang, et al.. (2021). Newly regenerated axons via scaffolds promote sub-lesional reorganization and motor recovery with epidural electrical stimulation. npj Regenerative Medicine. 6(1). 66–66. 19 indexed citations

3.

Moinuddin, F. M., Yagiz U. Yolcu, Waseem Wahood, et al.. (2020). Early and sustained improvements in motor function in rats after infusion of allogeneic umbilical cord-derived mesenchymal stem cells following spinal cord injury. Spinal Cord. 59(3). 319–327. 5 indexed citations

4.

Siddiqui, Ahad M., Peter J. Grahn, Bingkun K. Chen, et al.. (2020). The Translesional Spinal Network and Its Reorganization after Spinal Cord Injury. The Neuroscientist. 28(2). 163–179. 19 indexed citations

5.

Chen, Bingkun K., et al.. (2019). Combinatorial tissue engineering partially restores function after spinal cord injury. Journal of Tissue Engineering and Regenerative Medicine. 13(5). 857–873. 20 indexed citations

6.

Chen, Bingkun K., Nicolas N. Madigan, Mahrokh Dadsetan, et al.. (2017). GDNF Schwann cells in hydrogel scaffolds promote regional axon regeneration, remyelination and functional improvement after spinal cord transection in rats. Journal of Tissue Engineering and Regenerative Medicine. 12(1). e398–e407. 52 indexed citations

7.

Grahn, Peter J., Bingkun K. Chen, Andrew M. Knight, et al.. (2015). Positively Charged Oligo[Poly(Ethylene Glycol) Fumarate] Scaffold Implantation Results in a Permissive Lesion Environment after Spinal Cord Injury in Rat. Tissue Engineering Part A. 21(13-14). 2099–2114. 40 indexed citations

8.

Grahn, Peter J., Bingkun K. Chen, Andrew M. Knight, et al.. (2015). Positively Charged Oligo[Poly(Ethylene Glycol) Fumarate] Scaffold Implantation Results in a Permissive Lesion Environment after Spinal Cord Injury in Rat. Tissue Engineering Part A. 1219501877–1219501877. 3 indexed citations

9.

Madigan, Nicolas N., Bingkun K. Chen, Andrew M. Knight, et al.. (2014). Comparison of Cellular Architecture, Axonal Growth, and Blood Vessel Formation Through Cell-Loaded Polymer Scaffolds in the Transected Rat Spinal Cord. Tissue Engineering Part A. 20(21-22). 2985–2997. 30 indexed citations

10.

Grahn, Peter J., Sandeep Vaishya, Andrew M. Knight, et al.. (2014). Implantation of cauda equina nerve roots through a biodegradable scaffold at the conus medullaris in rat. The Spine Journal. 14(9). 2172–2177. 6 indexed citations

11.

Chen, Bingkun K., Nathan P. Staff, Andrew M. Knight, et al.. (2014). A safety study on intrathecal delivery of autologous mesenchymal stromal cells in rabbits directly supporting Phase I human trials. Transfusion. 55(5). 1013–1020. 28 indexed citations

12.

Cloud, Beth A., et al.. (2012). Hemisection spinal cord injury in rat: The value of intraoperative somatosensory evoked potential monitoring. Journal of Neuroscience Methods. 211(2). 179–184. 17 indexed citations

13.

Chen, Bingkun K., Andrew M. Knight, Nicolas N. Madigan, et al.. (2011). Comparison of polymer scaffolds in rat spinal cord: A step toward quantitative assessment of combinatorial approaches to spinal cord repair. Biomaterials. 32(32). 8077–8086. 61 indexed citations

14.

Chen, Bingkun K., Steven M. Miller, Carlos B. Mantilla, et al.. (2006). Optimizing conditions and avoiding pitfalls for prolonged axonal tracing with carbocyanine dyes in fixed rat spinal cords. Journal of Neuroscience Methods. 154(1-2). 256–263. 12 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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