Daniel I. Messinger

1.5k total citations
15 papers, 1.2k citations indexed

About

Daniel I. Messinger is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Ecology. According to data from OpenAlex, Daniel I. Messinger has authored 15 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cellular and Molecular Neuroscience, 7 papers in Molecular Biology and 6 papers in Ecology. Recurrent topics in Daniel I. Messinger's work include Neurobiology and Insect Physiology Research (7 papers), Receptor Mechanisms and Signaling (5 papers) and Crustacean biology and ecology (5 papers). Daniel I. Messinger is often cited by papers focused on Neurobiology and Insect Physiology Research (7 papers), Receptor Mechanisms and Signaling (5 papers) and Crustacean biology and ecology (5 papers). Daniel I. Messinger collaborates with scholars based in United States, Bulgaria and Czechia. Daniel I. Messinger's co-authors include Charles Chavkin, Andrew E. Christie, Selena S. Schattauer, Michael R. Bruchas, Benjamin B. Land, Yun‐Wei A. Hsu, Julia C. Lemos, Horacio O. de la Iglesia, Patsy S. Dickinson and Elizabeth A. Stemmler and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and Journal of Neuroscience.

In The Last Decade

Daniel I. Messinger

15 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel I. Messinger United States 14 993 577 220 123 101 15 1.2k
Yuko Fujisawa Japan 20 763 0.8× 497 0.9× 98 0.4× 26 0.2× 53 0.5× 39 1.7k
Vincenzina Reale United Kingdom 19 1.9k 1.9× 1.4k 2.4× 73 0.3× 33 0.3× 162 1.6× 33 2.6k
Ildikó Kemenes United Kingdom 21 696 0.7× 276 0.5× 180 0.8× 26 0.2× 88 0.9× 43 1.1k
Nikolai Dembrow United States 18 920 0.9× 390 0.7× 108 0.5× 26 0.2× 46 0.5× 22 1.3k
Matthew J. Brierley United Kingdom 18 356 0.4× 167 0.3× 130 0.6× 37 0.3× 71 0.7× 19 718
Anibal Cravchik United States 15 1.5k 1.5× 600 1.0× 68 0.3× 64 0.5× 57 0.6× 19 2.8k
Benoît Malpaux France 34 457 0.5× 547 0.9× 70 0.3× 89 0.7× 321 3.2× 74 3.0k
Tom Janssen Belgium 25 842 0.8× 445 0.8× 159 0.7× 9 0.1× 158 1.6× 42 1.7k
Steven L. McIntire United States 21 906 0.9× 1.2k 2.0× 95 0.4× 36 0.3× 399 4.0× 25 2.8k
Marcello Brunelli Italy 25 1.2k 1.3× 675 1.2× 87 0.4× 67 0.5× 165 1.6× 77 1.8k

Countries citing papers authored by Daniel I. Messinger

Since Specialization
Citations

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

Fields of papers citing papers by Daniel I. Messinger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel I. Messinger. 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 Daniel I. Messinger. The network helps show where Daniel I. Messinger may publish in the future.

Co-authorship network of co-authors of Daniel I. Messinger

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

All Works

15 of 15 papers shown
1.
Messinger, Daniel I., Selena S. Schattauer, Larry S. Zweifel, et al.. (2015). Kappa Opioid Receptor-Induced Aversion Requires p38 MAPK Activation in VTA Dopamine Neurons. Journal of Neuroscience. 35(37). 12917–12931. 143 indexed citations
2.
Lemos, Julia C., et al.. (2012). Repeated Stress Dysregulates κ-Opioid Receptor Signaling in the Dorsal Raphe through a p38α MAPK-Dependent Mechanism. Journal of Neuroscience. 32(36). 12325–12336. 47 indexed citations
3.
Schindler, Abigail G., Daniel I. Messinger, Jeffrey S. Smith, et al.. (2012). Stress Produces Aversion and Potentiates Cocaine Reward by Releasing Endogenous Dynorphins in the Ventral Striatum to Locally Stimulate Serotonin Reuptake. Journal of Neuroscience. 32(49). 17582–17596. 93 indexed citations
4.
Bruchas, Michael R., Abigail G. Schindler, Haripriya Shankar, et al.. (2011). Selective p38α MAPK Deletion in Serotonergic Neurons Produces Stress Resilience in Models of Depression and Addiction. Neuron. 71(3). 498–511. 215 indexed citations
5.
Land, Benjamin B., Michael R. Bruchas, Selena S. Schattauer, et al.. (2009). Activation of the kappa opioid receptor in the dorsal raphe nucleus mediates the aversive effects of stress and reinstates drug seeking. Proceedings of the National Academy of Sciences. 106(45). 19168–19173. 237 indexed citations
6.
Hsu, Yun‐Wei A., Elizabeth A. Stemmler, Daniel I. Messinger, et al.. (2008). Cloning and differential expression of two β‐pigment‐dispersing hormone (β‐PDH) isoforms in the crab Cancer productus: Evidence for authentic β‐PDH as a local neurotransmitter and β‐PDH II as a humoral factor. The Journal of Comparative Neurology. 508(2). 197–211. 33 indexed citations
7.
Verley, Derek R., et al.. (2008). Characteristic differences in modulation of stomatogastric musculature by a neuropeptide in three species of Cancer crabs. Journal of Comparative Physiology A. 194(10). 879–886. 8 indexed citations
8.
Stemmler, Elizabeth A., Yun‐Wei A. Hsu, Christopher R. Cashman, et al.. (2007). Direct tissue MALDI-FTMS profiling of individual Cancer productus sinus glands reveals that one of three distinct combinations of crustacean hyperglycemic hormone precursor-related peptide (CPRP) isoforms are present in individual crabs. General and Comparative Endocrinology. 154(1-3). 184–192. 14 indexed citations
9.
Stemmler, Elizabeth A., Christopher R. Cashman, Daniel I. Messinger, et al.. (2007). High-mass-resolution direct-tissue MALDI-FTMS reveals broad conservation of three neuropeptides (APSGFLGMRamide, GYRKPPFNGSIFamide and pQDLDHVFLRFamide) across members of seven decapod crustaean infraorders. Peptides. 28(11). 2104–2115. 73 indexed citations
10.
11.
Christie, Andrew E., Elizabeth A. Stemmler, Daniel I. Messinger, et al.. (2006). Identification, physiological actions, and distribution of VYRKPPFNGSIFamide (Val1‐SIFamide) in the stomatogastric nervous system of the American lobster Homarus americanus. The Journal of Comparative Neurology. 496(3). 406–421. 57 indexed citations
12.
13.
Fu, Qiang, Yun‐Wei A. Hsu, Daniel I. Messinger, et al.. (2005). Hormone complement of the Cancer productus sinus gland and pericardial organ: An anatomical and mass spectrometric investigation. The Journal of Comparative Neurology. 493(4). 607–626. 121 indexed citations
14.
Verley, Derek R., et al.. (2005). Bistable Behavior Originating in the Axon of a Crustacean Motor Neuron. Journal of Neurophysiology. 95(3). 1356–1368. 22 indexed citations
15.
Messinger, Daniel I., Derek R. Verley, Yun‐Wei A. Hsu, et al.. (2005). Identification and characterization of a tachykinin-containing neuroendocrine organ in the commissural ganglion of the crabCancer productus. Journal of Experimental Biology. 208(17). 3303–3319. 42 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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