David J. Poulsen

2.1k total citations
50 papers, 1.6k citations indexed

About

David J. Poulsen is a scholar working on Molecular Biology, Neurology and Epidemiology. According to data from OpenAlex, David J. Poulsen has authored 50 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 15 papers in Neurology and 13 papers in Epidemiology. Recurrent topics in David J. Poulsen's work include Traumatic Brain Injury and Neurovascular Disturbances (13 papers), Neuroinflammation and Neurodegeneration Mechanisms (10 papers) and Neuroscience and Neuropharmacology Research (10 papers). David J. Poulsen is often cited by papers focused on Traumatic Brain Injury and Neurovascular Disturbances (13 papers), Neuroinflammation and Neurodegeneration Mechanisms (10 papers) and Neuroscience and Neuropharmacology Research (10 papers). David J. Poulsen collaborates with scholars based in United States, Finland and China. David J. Poulsen's co-authors include Thomas Rau, Angelo C. Lepore, Tamara J. Hala, Hai‐Ying Shen, Detlev Boison, Diane M. Brooks, Linda Overstreet‐Wadiche, Jacques I. Wadiche, Jessica H. Chancey and Matthew J. During and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Neuron.

In The Last Decade

David J. Poulsen

50 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David J. Poulsen United States 24 622 586 281 254 207 50 1.6k
Sara Cipriani Italy 21 438 0.7× 347 0.6× 447 1.6× 201 0.8× 228 1.1× 28 1.7k
Yi Fan China 28 1.1k 1.7× 630 1.1× 480 1.7× 359 1.4× 180 0.9× 61 2.1k
Trevor J. Bushell United Kingdom 23 793 1.3× 833 1.4× 470 1.7× 125 0.5× 239 1.2× 52 2.1k
P.C. Barber United Kingdom 27 714 1.1× 889 1.5× 210 0.7× 282 1.1× 348 1.7× 50 2.4k
R.A. Gadient United States 22 862 1.4× 754 1.3× 609 2.2× 149 0.6× 329 1.6× 24 2.6k
G. Aleph Prieto United States 21 496 0.8× 483 0.8× 428 1.5× 157 0.6× 136 0.7× 32 1.6k
Noel G. Carlson United States 31 1.2k 2.0× 562 1.0× 584 2.1× 412 1.6× 173 0.8× 79 2.8k
Ramendra N. Saha United States 19 1.1k 1.7× 509 0.9× 534 1.9× 136 0.5× 179 0.9× 28 2.2k
Karianne Schuurman Netherlands 24 914 1.5× 442 0.8× 695 2.5× 123 0.5× 141 0.7× 33 2.3k
Lisheng Peng China 25 786 1.3× 712 1.2× 290 1.0× 660 2.6× 79 0.4× 67 2.0k

Countries citing papers authored by David J. Poulsen

Since Specialization
Citations

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

Fields of papers citing papers by David J. Poulsen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J. Poulsen. 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 David J. Poulsen. The network helps show where David J. Poulsen may publish in the future.

Co-authorship network of co-authors of David J. Poulsen

This figure shows the co-authorship network connecting the top 25 collaborators of David J. Poulsen. A scholar is included among the top collaborators of David J. Poulsen 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 David J. Poulsen. David J. Poulsen 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.
Schweser, Ferdinand, et al.. (2022). Differential Patterns of Change in Brain Connectivity Resulting from Severe Traumatic Brain Injury. Brain Connectivity. 12(9). 799–811. 5 indexed citations
2.
Shen, Shichen, Xue Wang, Xiaoyu Zhu, et al.. (2022). High-quality and robust protein quantification in large clinical/pharmaceutical cohorts with IonStar proteomics investigation. Nature Protocols. 18(3). 700–731. 13 indexed citations
3.
Shen, Shichen, et al.. (2021). Potential Neuroprotective Mechanisms of Methamphetamine Treatment in Traumatic Brain Injury Defined by Large-Scale IonStar-Based Quantitative Proteomics. International Journal of Molecular Sciences. 22(5). 2246–2246. 4 indexed citations
4.
Lipponen, Anssi, et al.. (2019). Extracellular Vesicles as Diagnostics and Therapeutics for Structural Epilepsies. International Journal of Molecular Sciences. 20(6). 1259–1259. 23 indexed citations
5.
Shen, Xiaomeng, Shichen Shen, Jun Li, et al.. (2018). IonStar enables high-precision, low-missing-data proteomics quantification in large biological cohorts. Proceedings of the National Academy of Sciences. 115(21). E4767–E4776. 62 indexed citations
6.
Haider, Mohammad N., et al.. (2018). Intracranial pressure changes after mild traumatic brain injury: a systematic review. Brain Injury. 32(7). 809–815. 26 indexed citations
7.
Falnikar, Aditi, Tamara J. Hala, David J. Poulsen, & Angelo C. Lepore. (2015). GLT1 overexpression reverses established neuropathic pain‐related behavior and attenuates chronic dorsal horn neuron activation following cervical spinal cord injury. Glia. 64(3). 396–406. 56 indexed citations
8.
Rau, Thomas, John A. Ziemniak, & David J. Poulsen. (2015). The neuroprotective potential of low-dose methamphetamine in preclinical models of stroke and traumatic brain injury. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 64. 231–236. 22 indexed citations
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Lü, Qing, Thomas Rau, Valerie Harris, et al.. (2011). Increased p38 mitogen-activated protein kinase signaling is involved in the oxidative stress associated with oxygen and glucose deprivation in neonatal hippocampal slice cultures. European Journal of Neuroscience. 34(7). 1093–1101. 40 indexed citations
12.
Theofilas, Panos, K. Stewart, Hai‐Ying Shen, et al.. (2011). Adenosine kinase as a target for therapeutic antisense strategies in epilepsy. Epilepsia. 52(3). 589–601. 75 indexed citations
13.
Rau, Thomas, Li Zhang, Diane M. Brooks, et al.. (2011). Low dose methamphetamine mediates neuroprotection through a PI3K-AKT pathway. Neuropharmacology. 61(4). 677–686. 44 indexed citations
14.
Luebke, Anne E., et al.. (2009). Adenoviral and AAV-Mediated Gene Transfer to the Inner Ear: Role of Serotype, Promoter, and Viral Load on In Vivo and In Vitro Infection Efficiencies. Advances in oto-rhino-laryngology. 66. 87–98. 23 indexed citations
15.
Peterson, Karin E., Susan S. Pourciau, Min Du, et al.. (2008). Neurovirulence of Polytropic Murine Retrovirus Is Influenced by Two Separate Regions on Opposite Sides of the Envelope Protein Receptor Binding Domain. Journal of Virology. 82(17). 8906–8910. 5 indexed citations
16.
17.
Lurie, Diana I., et al.. (2005). Adeno-associated virus-mediated gene transfer to hair cells and support cells of the murine cochlea. Molecular Therapy. 11(6). 843–848. 65 indexed citations
18.
Babcock, Alex M., et al.. (2005). In vivo Inhibition of Hippocampal Ca2+/Calmodulin-Dependent Protein Kinase II by RNA Interference. Molecular Therapy. 11(6). 899–905. 23 indexed citations
19.
Poulsen, David J., Shelly J. Robertson, Cynthia Favara, John L. Portis, & Bruce Chesebro. (1998). Mapping of a Neurovirulence Determinant within the Envelope Protein of a Polytropic Murine Retrovirus: Induction of Central Nervous System Disease by Low Levels of Virus. Virology. 248(2). 199–207. 23 indexed citations
20.
Poulsen, David J., et al.. (1991). Identification of the infectious laryngotracheitis virus glycoprotein gB gene by the polymerase chain reaction. Virus Genes. 5(4). 335–347. 16 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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