Zoltán Máté

3.1k citations
31 papers · 1.8k · h-index 19

Impact in

Papers in

Zoltán Máté

30 papers receiving 1.8k citations

Peers

Zoltán Máté
Comparison fields: 5 of 116
  • Cellular and Molecular Neuroscience 382
  • Plant Science 799
  • Molecular Biology 1.0k
  • Neurology 97
  • Cognitive Neuroscience 219
Replace Jane Kuk with:
Jane Kuk United States
Tsuyoshi Hirota Japan
Claudia S. Bauer United Kingdom
Charles A. Peto United States
Nicholas Gekakis United States
Jodi Maple‐Grødem Norway
Bertram Schmitt Germany
Corinne Sidler Switzerland
Lino Sáez United States
Mayumi Nakamura Japan
Zoltán Máté relative to Jane Kuk United States Jane Kuk's profile →
Citations per field
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Citations per year

Countries citing papers authored by Zoltán Máté

Since Specialization
Citations

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

Fields of papers citing papers by Zoltán Máté

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Zoltán Máté, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Zoltán Máté Line = papers co-authored together Zoltán Máté links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004409
2 2006304
3 2015267
4 1997101
5 201477
6 199875
7 201473
8 200362
9 200847
10 200939
11 201536
12 202134
13 202133
14 201931
15 201728
16 200026
17 202124
18 201423
19 201321
20 201616

About Zoltán Máté

Zoltán Máté is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Plant Science, Cognitive Neuroscience and Pharmacology, having authored 31 papers that have together received 1.8k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (11 papers), Photosynthetic Processes and Mechanisms (9 papers), Light effects on plants (9 papers), Algal biology and biofuel production (5 papers), Cannabis and Cannabinoid Research (5 papers), Memory and Neural Mechanisms (5 papers), Neuroinflammation and Neurodegeneration Mechanisms (4 papers) and Neuropeptides and Animal Physiology (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (382 citations), Plant Science (799 citations), Molecular Biology (1.0k citations), Neurology (97 citations) and Cognitive Neuroscience (219 citations). Zoltán Máté has collaborated with scholars based in Hungary, Germany and United States. Frequent co-authors include Ferenc Nagy, Roman Ulm, Attila Oravecz, Eberhard Schäfer, Alexander Baumann, Edward J. Oakeley, Éva Ádám, Gábor Szabó, Imre Vass and Tibor Harkany. Their work appears in journals such as Photosynthesis Research, Brain Structure and Function, Nature Communications, The FASEB Journal and ACS Omega.

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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