Camron D. Bryant

3.0k total citations
63 papers, 1.8k citations indexed

About

Camron D. Bryant is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Physiology. According to data from OpenAlex, Camron D. Bryant has authored 63 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Cellular and Molecular Neuroscience, 28 papers in Molecular Biology and 16 papers in Physiology. Recurrent topics in Camron D. Bryant's work include Neurotransmitter Receptor Influence on Behavior (21 papers), Receptor Mechanisms and Signaling (15 papers) and Neuropeptides and Animal Physiology (12 papers). Camron D. Bryant is often cited by papers focused on Neurotransmitter Receptor Influence on Behavior (21 papers), Receptor Mechanisms and Signaling (15 papers) and Neuropeptides and Animal Physiology (12 papers). Camron D. Bryant collaborates with scholars based in United States, United Kingdom and France. Camron D. Bryant's co-authors include Christopher J. Evans, Shoshana Eitan, Abraham A. Palmer, Yu Chi Yang, Michael S. Fanselow, Greta Sokoloff, Kabirullah Lutfy, F. Ivy Carroll, Hiroshi Takeshima and Nigel T. Maidment and has published in prestigious journals such as Journal of Neuroscience, SHILAP Revista de lepidopterología and Nature Neuroscience.

In The Last Decade

Camron D. Bryant

59 papers receiving 1.7k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Camron D. Bryant 746 682 554 251 164 63 1.8k
Susan C. McQuown 584 0.8× 1.2k 1.8× 435 0.8× 351 1.4× 86 0.5× 16 2.0k
Julie Le Merrer 1.1k 1.5× 1.0k 1.5× 359 0.6× 188 0.7× 202 1.2× 38 2.2k
Jérôme A. J. Becker 1.4k 1.8× 1.3k 1.9× 475 0.9× 176 0.7× 193 1.2× 42 2.4k
J.F. Cubells 899 1.2× 491 0.7× 254 0.5× 195 0.8× 76 0.5× 21 2.0k
Mechthild Voits 806 1.1× 463 0.7× 383 0.7× 115 0.5× 316 1.9× 19 2.0k
Bettina Bert 607 0.8× 448 0.7× 197 0.4× 134 0.5× 97 0.6× 56 1.8k
Daniela D. Pollak 571 0.8× 686 1.0× 301 0.5× 142 0.6× 253 1.5× 77 2.5k
Vanya Quiñones-Jenab 1.3k 1.7× 471 0.7× 326 0.6× 219 0.9× 195 1.2× 60 2.2k
Shirzad Jenab 1.4k 1.9× 805 1.2× 470 0.8× 198 0.8× 176 1.1× 78 2.4k
Elena Martín‐García 1.0k 1.4× 734 1.1× 252 0.5× 213 0.8× 287 1.8× 70 2.4k

Countries citing papers authored by Camron D. Bryant

Since Specialization
Citations

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

Fields of papers citing papers by Camron D. Bryant

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Camron D. Bryant. 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 Camron D. Bryant. The network helps show where Camron D. Bryant may publish in the future.

Co-authorship network of co-authors of Camron D. Bryant

This figure shows the co-authorship network connecting the top 25 collaborators of Camron D. Bryant. A scholar is included among the top collaborators of Camron D. Bryant 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 Camron D. Bryant. Camron D. Bryant 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.
Lynch, William B., Britahny M. Baskin, Martin T. Ferris, et al.. (2025). Validation studies and multiomics analysis of Zhx2 as a candidate quantitative trait gene underlying brain oxycodone metabolite (oxymorphone) levels and behavior. Journal of Pharmacology and Experimental Therapeutics. 392(5). 103557–103557. 1 indexed citations
2.
Lee, Edward C., E. J. Feng, David Kotlyar, et al.. (2025). Cross-Sensitization between Binge Eating and Binge Drinking in a Novel C57BL/6NJ Murine Model of Disease Comorbidity Requires PDE4B Activation. Journal of Neuroscience. 45(16). e1810242025–e1810242025. 1 indexed citations
3.
Lynch, William B., et al.. (2025). The striatal heterogeneous nuclear ribonucleoprotein H1 mRNA targetome associated with methamphetamine administration and behavior. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 144. 111598–111598.
4.
Goldberg, Lisa R., Aswathy Sebastian, Craig A. Praul, et al.. (2024). Alcohol and fear conditioning produce strain‐specific changes in the dorsal hippocampal transcriptome of adolescent C57BL/6J and DBA/2J mice. Alcohol Clinical and Experimental Research. 48(11). 2022–2034.
5.
Caillaud, Martial, et al.. (2022). Comparison of Pain-Like behaviors in two surgical incision animal models in C57BL/6J mice. SHILAP Revista de lepidopterología. 12. 100103–100103. 6 indexed citations
6.
Williams, Benjamin R., et al.. (2022). A Glitch in the Matrix: The Role of Extracellular Matrix Remodeling in Opioid Use Disorder. Frontiers in Integrative Neuroscience. 16. 899637–899637. 17 indexed citations
7.
Yen, William, R.K. Babbs, Ryan W. Logan, et al.. (2021). Sex Differences in Behavioral and Brainstem Transcriptomic Neuroadaptations following Neonatal Opioid Exposure in Outbred Mice. eNeuro. 8(5). ENEURO.0143–21.2021. 20 indexed citations
8.
Babbs, R.K., et al.. (2021). Systems genetic analysis of binge‐like eating in a C57BL/6J x DBA/2J‐F2 cross. Genes Brain & Behavior. 20(6). 5 indexed citations
9.
Goldberg, Lisa R., Eric Reed, W. Evan Johnson, et al.. (2021). A quantitative trait variant in Gabra2 underlies increased methamphetamine stimulant sensitivity. Genes Brain & Behavior. 20(8). e12774–e12774. 3 indexed citations
10.
Warncke, Urszula Osinska, Wisam Toma, Martial Caillaud, et al.. (2021). Impact of Dose, Sex, and Strain on Oxaliplatin-Induced Peripheral Neuropathy in Mice. SHILAP Revista de lepidopterología. 2. 683168–683168. 30 indexed citations
11.
Caillaud, Martial, et al.. (2020). C57BL/6 substrain differences in formalin-induced pain-like behavioral responses. Behavioural Brain Research. 390. 112698–112698. 11 indexed citations
12.
Bryant, Camron D., et al.. (2020). The motivational valence of methamphetamine relates inversely to subsequent methamphetamine self-administration in female C57BL/6J mice. Behavioural Brain Research. 398. 112959–112959. 2 indexed citations
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15.
Bryant, Camron D., Deniz Bağdaş, Lisa R. Goldberg, et al.. (2019). C57BL/6 substrain differences in inflammatory and neuropathic nociception and genetic mapping of a major quantitative trait locus underlying acute thermal nociception. Molecular Pain. 15. 2224628822–2224628822. 24 indexed citations
16.
Yazdani, Neema, Ying Shen, W. Evan Johnson, & Camron D. Bryant. (2016). Striatal transcriptome analysis of a congenic mouse line (chromosome 11: 50–60Mb) exhibiting reduced methamphetamine sensitivity. Genomics Data. 8. 77–80. 3 indexed citations
17.
Bryant, Camron D., et al.. (2012). Methamphetamine-induced conditioned place preference in LG/J and SM/J mouse strains and an F45/F46 advanced intercross line. Frontiers in Genetics. 3. 126–126. 12 indexed citations
18.
Bryant, Camron D., et al.. (2009). Pavlovian conditioning of multiple opioid-like responses in mice. Drug and Alcohol Dependence. 103(1-2). 74–83. 33 indexed citations
19.
Bryant, Camron D., Margaret G. Distler, Michaelanne B. Munoz, et al.. (2008). A role for casein kinase 1 epsilon in the locomotor stimulant response to methamphetamine. Psychopharmacology. 203(4). 703–711. 35 indexed citations
20.
Bryant, Camron D., et al.. (2006). Morphine analgesic tolerance in 129P3/J and 129S6/SvEv mice. Pharmacology Biochemistry and Behavior. 85(4). 769–779. 11 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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