Martin Darvas

3.7k total citations
60 papers, 2.3k citations indexed

About

Martin Darvas is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Physiology. According to data from OpenAlex, Martin Darvas has authored 60 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Cellular and Molecular Neuroscience, 23 papers in Molecular Biology and 21 papers in Physiology. Recurrent topics in Martin Darvas's work include Alzheimer's disease research and treatments (17 papers), Neuroscience and Neuropharmacology Research (17 papers) and Neurotransmitter Receptor Influence on Behavior (13 papers). Martin Darvas is often cited by papers focused on Alzheimer's disease research and treatments (17 papers), Neuroscience and Neuropharmacology Research (17 papers) and Neurotransmitter Receptor Influence on Behavior (13 papers). Martin Darvas collaborates with scholars based in United States, Switzerland and France. Martin Darvas's co-authors include Richard D. Palmiter, Jonathan P. Fadok, Larry S. Zweifel, Jones G. Parker, Linda Van Aelst, Mario A. Penzo, Dimitri De Bundel, Bo Li, Vincent Robert and Luis F. Parada and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Martin Darvas

57 papers receiving 2.3k citations

Author Peers

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

Author Last Decade Papers Cites
Martin Darvas 1.1k 771 747 331 308 60 2.3k
Christopher Ford 1.9k 1.7× 730 0.9× 1.3k 1.8× 276 0.8× 192 0.6× 52 2.8k
Robyn M. Brown 1.3k 1.2× 877 1.1× 684 0.9× 379 1.1× 515 1.7× 87 2.8k
Elena Martín‐García 1.0k 0.9× 346 0.4× 734 1.0× 252 0.8× 287 0.9× 70 2.4k
Yajun Zhang 1.4k 1.2× 406 0.5× 1.0k 1.4× 259 0.8× 244 0.8× 34 2.4k
Jean‐Pierre Hornung 2.0k 1.8× 961 1.2× 1.1k 1.5× 289 0.9× 258 0.8× 61 3.6k
François Georges 2.6k 2.3× 1.1k 1.4× 1.1k 1.4× 399 1.2× 338 1.1× 50 3.6k
Richard H. Dyck 1.4k 1.3× 794 1.0× 1.1k 1.5× 472 1.4× 201 0.7× 82 3.5k
Kyriaki Sidiropoulou 766 0.7× 508 0.7× 485 0.6× 172 0.5× 329 1.1× 42 1.7k
Janusz Moryś 1.2k 1.1× 746 1.0× 648 0.9× 493 1.5× 132 0.4× 178 2.9k
Edward G. Meloni 1.5k 1.4× 651 0.8× 887 1.2× 274 0.8× 153 0.5× 37 2.7k

Countries citing papers authored by Martin Darvas

Since Specialization
Citations

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

Fields of papers citing papers by Martin Darvas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Darvas. 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 Martin Darvas. The network helps show where Martin Darvas may publish in the future.

Co-authorship network of co-authors of Martin Darvas

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Darvas. A scholar is included among the top collaborators of Martin Darvas 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 Martin Darvas. Martin Darvas 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.
Zhu, Lei, Martin Darvas, Paul V. Sabatini, et al.. (2025). Mesolimbic dopamine neurons drive infradian rhythms in sleep-wake and heightened activity state. Science Advances. 11(1). eado9965–eado9965. 3 indexed citations
2.
McGrath, Stephanie, Matthew D. Dunbar, Evan L. MacLean, et al.. (2025). The companion dog as a translational model for Alzheimer's disease: Development of a longitudinal research platform and post mortem protocols. Alzheimer s & Dementia. 21(9). e70630–e70630.
3.
Fisher, Daniel, Pamela J. McMillan, Mary A. Valentine, et al.. (2025). Performance of novel tau antibodies across multiple modalities for Alzheimer's disease assessment. Alzheimer s & Dementia. 21(7). e70481–e70481.
4.
McGrath, Stephanie, et al.. (2025). Plasma and cerebrospinal fluid biomarkers in aged dogs with cognitive decline. BMC Veterinary Research. 21(1). 617–617.
5.
6.
Bray, Emily E., Stephanie McGrath, Gene E. Alexander, et al.. (2024). Characterizing dog cognitive aging using spontaneous problem-solving measures: development of a battery of tests from the Dog Aging Project. GeroScience. 47(1). 23–43. 1 indexed citations
7.
Urfer, Silvan R., Martin Darvas, Daniel Promislow, et al.. (2021). Canine Cognitive Dysfunction (CCD) scores correlate with amyloid beta 42 levels in dog brain tissue. GeroScience. 43(5). 2379–2386. 32 indexed citations
8.
Wainberg, Michael, David M. Koelle, Ben Readhead, et al.. (2021). The viral hypothesis: how herpesviruses may contribute to Alzheimer’s disease. Molecular Psychiatry. 26(10). 5476–5480. 34 indexed citations
9.
Chen, Sunny, Lesley Leong, Aleen D. Saxton, et al.. (2020). Redefining transcriptional regulation of the APOE gene and its association with Alzheimer’s disease. PLoS ONE. 15(1). e0227667–e0227667. 35 indexed citations
10.
Darvas, Martin, et al.. (2020). A Geroscience Approach to Preventing Pathologic Consequences of COVID-19. Journal of Interferon & Cytokine Research. 40(9). 433–437. 1 indexed citations
11.
Wang, Yuhan, et al.. (2020). The antiparkinson drug ropinirole inhibits movement in a Parkinson's disease mouse model with residual dopamine neurons. Experimental Neurology. 333. 113427–113427. 8 indexed citations
12.
Fujita, Hirofumi, Avery C. Hunker, Martin Darvas, et al.. (2020). Purkinje Cell-Specific Knockout of Tyrosine Hydroxylase Impairs Cognitive Behaviors. Frontiers in Cellular Neuroscience. 14. 228–228. 27 indexed citations
13.
Huang, Ming, Martin Darvas, C. Dirk Keene, & Yinsheng Wang. (2019). Targeted Quantitative Proteomic Approach for High-Throughput Quantitative Profiling of Small GTPases in Brain Tissues of Alzheimer’s Disease Patients. Analytical Chemistry. 91(19). 12307–12314. 8 indexed citations
14.
Nguyen, Minh‐Thanh, Shruti Vemaraju, Gowri Nayak, et al.. (2019). An opsin 5–dopamine pathway mediates light-dependent vascular development in the eye. Nature Cell Biology. 21(4). 420–429. 62 indexed citations
15.
Noble, Emily E., Zhuo Wang, Clarissa M. Liu, et al.. (2019). Hypothalamus-hippocampus circuitry regulates impulsivity via melanin-concentrating hormone. Nature Communications. 10(1). 4923–4923. 57 indexed citations
16.
Lee, Amanda, et al.. (2019). Sleep-deprived cognitive impairment in aging mice is alleviated by rapamycin. PubMed. 1(1). 5–9. 7 indexed citations
17.
Keene, C. Dirk, et al.. (2018). Luminex-based quantification of Alzheimer's disease neuropathologic change in formalin-fixed post-mortem human brain tissue. Laboratory Investigation. 99(7). 1056–1067. 8 indexed citations
18.
19.
Yuan, Jie, Martin Darvas, Bethany N. Sotak, et al.. (2010). Dopamine is not essential for the development of methamphetamine‐induced neurotoxicity. Journal of Neurochemistry. 114(4). 1135–1142. 9 indexed citations
20.
Darvas, Martin & Richard D. Palmiter. (2010). Contributions of Striatal Dopamine Signaling to the Modulation of Cognitive Flexibility. Biological Psychiatry. 69(7). 704–707. 49 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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