Júlia Koller

28 papers receiving 511 citations

Peers

Júlia Koller
Comparison fields: 5 of 99
  • Endocrine and Autonomic Systems 77
  • Behavioral Neuroscience 20
  • Cellular and Molecular Neuroscience 80
  • Computational Theory and Mathematics 70
  • Cell Biology 47
Replace Cathalijn H. C. Leenaars with:
Cathalijn H. C. Leenaars Netherlands
Xinan Liu China
Tatjana Petrov Switzerland
Hui Hua Chang Taiwan
Yuanyuan Hou China
Noel Boyle United States
Anant Jain United States
Ihn-Geun Choi South Korea
Kenneth Yun United States
Young United States
Júlia Koller relative to Cathalijn H. C. Leenaars Netherlands Cathalijn H. C. Leenaars's profile →
Citations per field
00.5×2.6×
Cathalijn H. C. Leenaars · 1×
Citations per year

Countries citing papers authored by Júlia Koller

Since Specialization
Citations

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

Fields of papers citing papers by Júlia Koller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Júlia Koller, 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 Júlia Koller Line = papers co-authored together Júlia Koller 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 201991
2 201789
3 201773
4 200655
5 201624
6 202323
7 202120
8 202019
9 202017
10 202117
11 201115
12 201014
13 201913
14 201112
15 202110
16 20229
17 20225
18 20164
19 20213
20 20243

About Júlia Koller

Júlia Koller is a scholar working on Endocrine and Autonomic Systems, Molecular Biology, Cellular and Molecular Neuroscience, Cardiology and Cardiovascular Medicine and Physiology, having authored 31 papers that have together received 530 indexed citations. Recurring topics across this work include Regulation of Appetite and Obesity (4 papers), Sociology and Education Studies (3 papers), Adipose Tissue and Metabolism (3 papers), Education Methods and Technologies (2 papers), Computational Drug Discovery Methods (2 papers), Pancreatic function and diabetes (2 papers), Neuropeptides and Animal Physiology (2 papers) and Innovation, Technology, and Society (1 paper). The work is most often cited by research in Endocrine and Autonomic Systems (77 citations), Behavioral Neuroscience (20 citations), Cellular and Molecular Neuroscience (80 citations), Computational Theory and Mathematics (70 citations) and Cell Biology (47 citations). Júlia Koller has collaborated with scholars based in Hungary, Australia and Germany. Frequent co-authors include Krisztián Búza, Ladislav Peška, Herbert Herzog, Lei Zhang, J. Solà, Olivier Chételat, Jean Luprano, Yue Qi, Chi Kin Ip and Yan‐Chuan Shi. Their work appears in journals such as Neuropeptides, Acta Polytechnica Hungarica, European Child & Adolescent Psychiatry, Human Genetics and PLoS ONE.

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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