Michael T. McCoy

14.3k total citations · 1 hit paper
66 papers, 12.2k citations indexed

About

Michael T. McCoy is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Surgery. According to data from OpenAlex, Michael T. McCoy has authored 66 papers receiving a total of 12.2k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Cellular and Molecular Neuroscience, 41 papers in Molecular Biology and 8 papers in Surgery. Recurrent topics in Michael T. McCoy's work include Neurotransmitter Receptor Influence on Behavior (26 papers), Neuroscience and Neuropharmacology Research (26 papers) and Receptor Mechanisms and Signaling (13 papers). Michael T. McCoy is often cited by papers focused on Neurotransmitter Receptor Influence on Behavior (26 papers), Neuroscience and Neuropharmacology Research (26 papers) and Receptor Mechanisms and Signaling (13 papers). Michael T. McCoy collaborates with scholars based in United States, France and Argentina. Michael T. McCoy's co-authors include Edward L. Schneider, Raymond R. Tice, Narendra P. Singh, Jean Lud Cadet, Subramaniam Jayanthi, Bruce Ladenheim, Irina N. Krasnova, Xiaolin Deng, Christie Brannock and Kevin G. Becker and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and PLoS ONE.

In The Last Decade

Michael T. McCoy

63 papers receiving 11.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A simple technique for quantitation of low levels of DNA damage in individual cells

1988 9.3k citations Narendra P. Singh, Michael T. McCoy et al. Experimental Cell Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael T. McCoy United States	32	4.0k	3.2k	3.0k	1.8k	1.6k	66	12.2k
Andreas Hartmann Germany	59	3.1k 0.8×	3.7k 1.1×	2.8k 0.9×	1.8k 1.0×	852 0.5×	245	14.9k
Emilio Rojas Mexico	51	5.4k 1.4×	2.8k 0.9×	2.5k 0.8×	1.5k 0.9×	2.2k 1.4×	188	12.3k
Daniel R. Doerge United States	68	3.9k 1.0×	1.7k 0.5×	2.8k 1.0×	2.4k 1.3×	323 0.2×	290	15.5k
Lucio G. Costa United States	69	3.7k 0.9×	1.3k 0.4×	4.8k 1.6×	5.3k 3.0×	2.2k 1.4×	328	17.8k
Narendra P. Singh United States	60	6.3k 1.6×	5.2k 1.6×	4.3k 1.5×	2.5k 1.4×	285 0.2×	174	19.7k
João Antônio Pêgas Henriques Brazil	59	4.1k 1.0×	1.6k 0.5×	1.3k 0.4×	2.2k 1.2×	390 0.2×	360	11.2k
T.M. Penning United States	76	8.4k 2.1×	2.4k 0.7×	1.9k 0.6×	719 0.4×	430 0.3×	353	21.0k
Jie Liu China	61	5.4k 1.4×	934 0.3×	2.6k 0.9×	1.2k 0.6×	1.5k 0.9×	461	17.5k
Pamela J. Lein United States	54	2.5k 0.6×	661 0.2×	2.5k 0.8×	1.8k 1.0×	2.2k 1.4×	252	9.4k
Lucia Migliore Italy	53	3.1k 0.8×	1.8k 0.6×	1.3k 0.4×	734 0.4×	347 0.2×	167	7.5k

Countries citing papers authored by Michael T. McCoy

Since Specialization

Citations

This map shows the geographic impact of Michael T. McCoy'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 Michael T. McCoy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael T. McCoy more than expected).

Fields of papers citing papers by Michael T. McCoy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael T. McCoy. 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 Michael T. McCoy. The network helps show where Michael T. McCoy may publish in the future.

Co-authorship network of co-authors of Michael T. McCoy

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

All Works

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20 of 20 papers shown

Jayanthi, Subramaniam, Bruce Ladenheim, Patricia Sullivan, et al.. (2022). Biochemical Neuroadaptations in the Rat Striatal Dopaminergic System after Prolonged Exposure to Methamphetamine Self-Administration. International Journal of Molecular Sciences. 23(17). 10092–10092. 11 indexed citations

Jayanthi, Subramaniam, et al.. (2022). Footshock-Induced Abstinence from Compulsive Methamphetamine Self-administration in Rat Model Is Accompanied by Increased Hippocampal Expression of Cannabinoid Receptors (CB1 and CB2). Molecular Neurobiology. 59(2). 1238–1248. 8 indexed citations

McCoy, Michael T., Subramaniam Jayanthi, & Jean Lud Cadet. (2021). Potassium Channels and Their Potential Roles in Substance Use Disorders. International Journal of Molecular Sciences. 22(3). 1249–1249. 15 indexed citations

Jayanthi, Subramaniam, Michael T. McCoy, & Jean Lud Cadet. (2021). Epigenetic Regulatory Dynamics in Models of Methamphetamine-Use Disorder. Genes. 12(10). 1614–1614. 14 indexed citations

McCoy, Michael T., et al.. (2020). Escalated Oxycodone Self-Administration and Punishment: Differential Expression of Opioid Receptors and Immediate Early Genes in the Rat Dorsal Striatum and Prefrontal Cortex. Frontiers in Neuroscience. 13. 1392–1392. 27 indexed citations

Torres, Oscar V., Subramaniam Jayanthi, Bruce Ladenheim, et al.. (2017). Compulsive methamphetamine taking under punishment is associated with greater cue-induced drug seeking in rats. Behavioural Brain Research. 326. 265–271. 32 indexed citations

Jayanthi, Subramaniam, Betina González, Michael T. McCoy, et al.. (2017). Methamphetamine Induces TET1- and TET3-Dependent DNA Hydroxymethylation of Crh and Avp Genes in the Rat Nucleus Accumbens. Molecular Neurobiology. 55(6). 5154–5166. 44 indexed citations

Torres, Oscar V., Bruce Ladenheim, Subramaniam Jayanthi, et al.. (2015). An Acute Methamphetamine Injection Downregulates the Expression of Several Histone Deacetylases (HDACs) in the Mouse Nucleus Accumbens: Potential Regulatory Role of HDAC2 Expression. Neurotoxicity Research. 30(1). 32–40. 19 indexed citations

Ladenheim, Bruce, et al.. (2014). Differential effects of binge methamphetamine injections on the mRNA expression of histone deacetylases (HDACs) in the rat striatum. NeuroToxicology. 45. 178–184. 27 indexed citations

10.

Krasnova, Irina N., Nathan J. Marchant, Bruce Ladenheim, et al.. (2014). Incubation of Methamphetamine and Palatable Food Craving after Punishment-Induced Abstinence. Neuropsychopharmacology. 39(8). 2008–2016. 103 indexed citations

11.

McCoy, Michael T., Bruce Ladenheim, Subramaniam Jayanthi, et al.. (2012). Chronic Methamphetamine Causes Differential Expression of Immediate Early Genes in the Nucleus Accumbens and Midbrain of Rats. PubMed. 1(1). 1–7.

12.

McCoy, Michael T., Subramaniam Jayanthi, Geneviève Beauvais, et al.. (2011). Chronic methamphetamine exposure suppresses the striatal expression of members of multiple families of immediate early genes (IEGs) in the rat: normalization by an acute methamphetamine injection. Psychopharmacology. 215(2). 353–365. 44 indexed citations

13.

Cadet, Jean Lud, Christie Brannock, Irina N. Krasnova, et al.. (2010). Methamphetamine-Induced Dopamine-Independent Alterations in Striatal Gene Expression in the 6-Hydroxydopamine Hemiparkinsonian Rats. PLoS ONE. 5(12). e15643–e15643. 30 indexed citations

14.

Cadet, Jean Lud, Christie Brannock, Bruce Ladenheim, et al.. (2010). Methamphetamine Preconditioning Causes Differential Changes in Striatal Transcriptional Responses to Large Doses of the Drug. Dose-Response. 9(2). 165–81. 20 indexed citations

15.

Cadet, Jean Lud, Irina N. Krasnova, Bruce Ladenheim, et al.. (2009). Methamphetamine Preconditioning: Differential Protective Effects on Monoaminergic Systems in the Rat Brain. Neurotoxicity Research. 15(3). 252–259. 31 indexed citations

16.

Jayanthi, Subramaniam, Michael T. McCoy, Geneviève Beauvais, et al.. (2009). Methamphetamine Induces Dopamine D1 Receptor-Dependent Endoplasmic Reticulum Stress-Related Molecular Events in the Rat Striatum. PLoS ONE. 4(6). e6092–e6092. 68 indexed citations

17.

Jayanthi, Subramaniam, et al.. (2001). Temporal profiling of methamphetamine‐induced changes in gene expression in the mouse brain: Evidence from cDNA array. Synapse. 41(1). 40–48. 90 indexed citations

18.

Holbrook, Nikki J., Rajesh Chopra, Michael T. McCoy, et al.. (1989). Expression of interleukin 2 and the interleukin 2 receptor in aging rats. Cellular Immunology. 120(1). 1–9. 30 indexed citations

19.

Nagel, Jürgen, Rajesh Chopra, Francis J. Chrest, et al.. (1988). Decreased proliferation, interleukin 2 synthesis, and interleukin 2 receptor expression are accompanied by decreased mRNA expression in phytohemagglutinin-stimulated cells from elderly donors.. Journal of Clinical Investigation. 81(4). 1096–1102. 217 indexed citations

20.

Singh, Narendra P., Michael T. McCoy, Raymond R. Tice, & Edward L. Schneider. (1988). A simple technique for quantitation of low levels of DNA damage in individual cells. Experimental Cell Research. 175(1). 184–191. 9305 indexed citations breakdown →

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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