Maxim Nikitchenko

527 citations
9 papers · 270 · h-index 6

Impact in

Papers in

Maxim Nikitchenko

7 papers receiving 262 citations

Peers

Maxim Nikitchenko
Comparison fields: 5 of 59
  • Cell Biology 133
  • Cognitive Neuroscience 97
  • Endocrine and Autonomic Systems 29
  • Cellular and Molecular Neuroscience 77
  • Biophysics 20
Replace Erin Song with:
Erin Song United States
Deepak Ailani Japan
Kristian J. Herrera United States
Gregory D. Marquart United States
Christoph Gebhardt France
Kristine E. Kolkman United States
Clemens Riegler United States
Thomas Panier France
Tatiana Gallego‐Flores United States
Noora Emilia Nevala United Kingdom
Maxim Nikitchenko relative to Erin Song United States Erin Song's profile →
Citations per field
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Erin Song · 1×
Citations per year

Countries citing papers authored by Maxim Nikitchenko

Since Specialization
Citations

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

Fields of papers citing papers by Maxim Nikitchenko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Maxim Nikitchenko, 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 Maxim Nikitchenko Line = papers co-authored together Maxim Nikitchenko links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 2018108
2 201953
3 201949
4 202231
5 202116
6 20087
7 20044
8
An expectation-maximization Fokker-Planck algorithm for the noisy integrate-and-fir e model
20072
9 20250

About Maxim Nikitchenko

Maxim Nikitchenko is a scholar working on Cognitive Neuroscience, Cell Biology, Ecology, Molecular Biology and Cellular and Molecular Neuroscience, having authored 9 papers that have together received 270 indexed citations. Recurring topics across this work include Zebrafish Biomedical Research Applications (4 papers), Neural dynamics and brain function (3 papers), Marine animal studies overview (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Neuroendocrine regulation and behavior (2 papers), Cephalopods and Marine Biology (1 paper), Animal Vocal Communication and Behavior (1 paper) and Advanced Chemical Physics Studies (1 paper). The work is most often cited by research in Cell Biology (133 citations), Cognitive Neuroscience (97 citations), Endocrine and Autonomic Systems (29 citations), Cellular and Molecular Neuroscience (77 citations) and Biophysics (20 citations). Maxim Nikitchenko has collaborated with scholars based in United States, Russia and United Kingdom. Frequent co-authors include Florian Engert, Owen Randlett, Misha B. Ahrens, Erin Song, Caroline Lei Wee, Aaron T. Kuan, Xiuye Chen, Yu Mu, Yu Hu and Alex Chen. Their work appears in journals such as Nature Communications, Current Biology, Nature Neuroscience, Neuron and Neural Computation.

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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