Brian J. Wainger

8.5k total citations · 5 hit papers
38 papers, 4.8k citations indexed

About

Brian J. Wainger is a scholar working on Molecular Biology, Physiology and Neurology. According to data from OpenAlex, Brian J. Wainger has authored 38 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 13 papers in Physiology and 10 papers in Neurology. Recurrent topics in Brian J. Wainger's work include Pain Mechanisms and Treatments (10 papers), Neurogenetic and Muscular Disorders Research (9 papers) and Amyotrophic Lateral Sclerosis Research (8 papers). Brian J. Wainger is often cited by papers focused on Pain Mechanisms and Treatments (10 papers), Neurogenetic and Muscular Disorders Research (9 papers) and Amyotrophic Lateral Sclerosis Research (8 papers). Brian J. Wainger collaborates with scholars based in United States, Netherlands and Germany. Brian J. Wainger's co-authors include Clifford J. Woolf, Kevin Eggan, Bina Santoro, Steven A. Siegelbaum, Seungkyu Lee, Justin K. Ichida, Gareth R. Tibbs, Matthew DeGennaro, Esther Son and Victor F. Rafuse and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Brian J. Wainger

37 papers receiving 4.7k citations

Hit Papers

A three-dimensional human neural cell culture model of Al... 2011 2026 2016 2021 2014 2013 2011 2014 2019 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian J. Wainger United States 19 2.9k 1.4k 947 927 648 38 4.8k
John Forsayeth United States 51 3.6k 1.2× 2.7k 1.9× 742 0.8× 1.2k 1.3× 535 0.8× 118 6.6k
Luís Pereira de Almeida Portugal 45 3.9k 1.4× 2.4k 1.7× 552 0.6× 848 0.9× 266 0.4× 148 6.1k
Andreas Hermann Germany 42 2.6k 0.9× 1.3k 0.9× 845 0.9× 1.7k 1.8× 1.7k 2.7× 241 5.8k
John Woulfe Canada 34 1.9k 0.7× 1.2k 0.9× 1.1k 1.2× 1.3k 1.5× 562 0.9× 119 4.8k
Junya Tanaka Japan 48 2.5k 0.9× 1.5k 1.0× 1.0k 1.1× 570 0.6× 277 0.4× 179 7.2k
Felipe A. Court Chile 42 3.2k 1.1× 2.4k 1.7× 882 0.9× 1.1k 1.2× 338 0.5× 88 6.3k
Thomas M. Wishart United Kingdom 31 1.9k 0.6× 951 0.7× 675 0.7× 418 0.5× 703 1.1× 80 3.2k
Chenghua Gu United States 42 3.7k 1.3× 2.9k 2.1× 582 0.6× 575 0.6× 213 0.3× 56 7.4k
Ronald P. Hart United States 50 4.1k 1.4× 1.7k 1.2× 613 0.6× 293 0.3× 300 0.5× 155 7.3k
Linda Greensmith United Kingdom 47 3.7k 1.3× 2.6k 1.9× 919 1.0× 3.3k 3.6× 2.0k 3.2× 152 7.8k

Countries citing papers authored by Brian J. Wainger

Since Specialization
Citations

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

Fields of papers citing papers by Brian J. Wainger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian J. Wainger

This figure shows the co-authorship network connecting the top 25 collaborators of Brian J. Wainger. A scholar is included among the top collaborators of Brian J. Wainger 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 Brian J. Wainger. Brian J. Wainger 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.
Weigel, Daniel J., Wen‐Chih Liu, Brian J. Wainger, et al.. (2024). Neuroma morphology: A macroscopic classification system. Muscle & Nerve. 70(6). 1172–1180. 1 indexed citations
2.
Li, Wenlu, Jingfei Shi, Zhanyang Yu, et al.. (2024). SLC22A17 as a Cell Death–Linked Regulator of Tight Junctions in Cerebral Ischemia. Stroke. 55(6). 1650–1659. 6 indexed citations
3.
Crane, Meredith J., et al.. (2024). Interleukin-1α links peripheral CaV2.2 channel activation to rapid adaptive increases in heat sensitivity in skin. Scientific Reports. 14(1). 9051–9051. 3 indexed citations
4.
Held, Aaron, Derek H. Oakley, Mark W. Albers, et al.. (2024). Neuronal STING activation in amyotrophic lateral sclerosis and frontotemporal dementia. Acta Neuropathologica. 147(1). 56–56. 21 indexed citations
5.
Liu, Wen‐Chih, et al.. (2024). Neuroma Analysis in Humans: Standardizing Sample Collection and Documentation. Journal of Surgical Research. 298. 185–192. 4 indexed citations
6.
Gee, Heon Yung, et al.. (2024). Distinct modulation of calcium-activated chloride channel TMEM16A by drug-binding sites. Proceedings of the National Academy of Sciences. 121(51). e2314011121–e2314011121. 3 indexed citations
7.
Held, Aaron, et al.. (2023). iPSC motor neurons, but not other derived cell types, capture gene expression changes in postmortem sporadic ALS motor neurons. Cell Reports. 42(9). 113046–113046. 10 indexed citations
9.
Dubreuil, D, et al.. (2021). A high-content platform for physiological profiling and unbiased classification of individual neurons. Cell Reports Methods. 1(1). 100004–100004. 6 indexed citations
10.
Pereira, João D., D Dubreuil, Aaron Held, et al.. (2021). Human sensorimotor organoids derived from healthy and amyotrophic lateral sclerosis stem cells form neuromuscular junctions. Nature Communications. 12(1). 4744–4744. 97 indexed citations
11.
Kiernan, Matthew C., Hugh Bostock, Susanna B. Park, et al.. (2019). Measurement of axonal excitability: Consensus guidelines. Clinical Neurophysiology. 131(1). 308–323. 67 indexed citations
12.
Wainger, Brian J., Elizabeth D. Buttermore, Júlia Teixeira Oliveira, et al.. (2014). Modeling pain in vitro using nociceptor neurons reprogrammed from fibroblasts. Nature Neuroscience. 18(1). 17–24. 164 indexed citations
14.
Wainger, Brian J., Evangelos Kiskinis, Ole Wiskow, et al.. (2014). Intrinsic Membrane Hyperexcitability of Amyotrophic Lateral Sclerosis Patient-Derived Motor Neurons. Cell Reports. 7(1). 1–11. 481 indexed citations breakdown →
15.
Yang, Yin, Shailesh Gupta, Kevin J. Kim, et al.. (2013). A Small Molecule Screen in Stem-Cell-Derived Motor Neurons Identifies a Kinase Inhibitor as a Candidate Therapeutic for ALS. Cell stem cell. 12(6). 713–726. 228 indexed citations
16.
Chiu, Isaac M., Balthasar A. Heesters, Nader Ghasemlou, et al.. (2013). Bacteria activate sensory neurons that modulate pain and inflammation. Nature. 501(7465). 52–57. 675 indexed citations breakdown →
17.
Son, Esther, Justin K. Ichida, Brian J. Wainger, et al.. (2011). Conversion of Mouse and Human Fibroblasts into Functional Spinal Motor Neurons. Cell stem cell. 9(3). 205–218. 508 indexed citations breakdown →
18.
Boulting, Gabriella L., Evangelos Kiskinis, Gist F. Croft, et al.. (2011). A functionally characterized test set of human induced pluripotent stem cells. Nature Biotechnology. 29(3). 279–286. 364 indexed citations
19.
Santoro, Bina, Brian J. Wainger, & Steven A. Siegelbaum. (2004). Regulation of HCN Channel Surface Expression by a Novel C-Terminal Protein-Protein Interaction. Journal of Neuroscience. 24(47). 10750–10762. 160 indexed citations
20.
Wainger, Brian J., Matthew DeGennaro, Bina Santoro, Steven A. Siegelbaum, & Gareth R. Tibbs. (2001). Molecular mechanism of cAMP modulation of HCN pacemaker channels. Nature. 411(6839). 805–810. 387 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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