Ulrich Egert

3.3k citations
55 papers · 2.5k indexed · h-index 26
Topics
Neuroscience and Neural Engineering (36 papers)Neural dynamics and brain function (34 papers)Neuroscience and Neuropharmacology Research (19 papers)

In The Last Decade

Ulrich Egert

53 papers receiving 2.4k citations

Peers

Ulrich Egert
Comparison fields: 5 of 106
  • Cellular and Molecular Neuroscience 1.8k
  • Cognitive Neuroscience 1.1k
  • Molecular Biology 510
  • Electrical and Electronic Engineering 462
  • Biomedical Engineering 440
Replace Yasuhiko Jimbo with:
Yasuhiko Jimbo Japan
Alfred Stett Germany
Luca Berdondini Italy
Udo Kraushaar Germany
Michela Chiappalone Italy
Douglas J. Bakkum Switzerland
Wim Rutten Netherlands
Urs Frey Switzerland
Mariateresa Tedesco Italy
Jennifer N. Gelinas United States
Ulrich Egert relative to Yasuhiko Jimbo Japan Yasuhiko Jimbo's profile →
Citations per field
00.5×1.5×
Yasuhiko Jimbo · 1×
Citations per year

Countries citing papers authored by Ulrich Egert

Since Specialization
Citations

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

Fields of papers citing papers by Ulrich Egert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ulrich Egert

This figure shows the co-authorship network connecting the top 25 collaborators of Ulrich Egert. A scholar is included among the top collaborators of Ulrich Egert 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 Ulrich Egert. Ulrich Egert 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
#WorkIndexed citations
1 9
2 5
3 40
4
Controlling biological neural networks with deep reinforcement learning.
1
5 25
6 15
7 22
8 39
9 13
10 28
11 136
12 21
13 9
14 168
15 52
16 50
17 60
18 155
19 92
20 40

About Ulrich Egert

Ulrich Egert is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Developmental Neuroscience, having authored 55 papers that have together received 2.5k indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (36 papers), Neural dynamics and brain function (34 papers) and Neuroscience and Neuropharmacology Research (19 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.8k citations), Cognitive Neuroscience (1.1k citations) and Electrochemistry (140 citations). Ulrich Egert has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include W. Nisch, Samora Okujeni, Marcel Halbach, Kathrin Banach, Hugo Hämmerle, Ad Aertsen, H. Haemmerle, Thomas Meyer, Alfred Stett and Elke Guenther. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and NeuroImage.

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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