K. V. Anokhin
- Cellular and Molecular Neuroscience top 2%
- Molecular Biology
- Cognitive Neuroscience top 5%
- Biophysics top 1%
- Physiology top 10%
- Co-authors
- Steven P. R. RoseА. А. ТиуноваА. М. ЖелтиковО. И. ИвашкинаA. B. FedotovLyubov V. AmitonovaИ. В. ФедотовIlya V. Fedotov
- Topics
- Memory and Neural Mechanisms (37 papers)Neuroscience and Neuropharmacology Research (31 papers)Photoreceptor and optogenetics research (28 papers)
- Partner nations
- RussiaUnited StatesUnited Kingdom
In The Last Decade
K. V. Anokhin
120 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 150
- Cellular and Molecular Neuroscience 727
- Molecular Biology 552
- Cognitive Neuroscience 434
- Biophysics 307
- Physiology 205
Countries citing papers authored by K. V. Anokhin
This map shows the geographic impact of K. V. Anokhin'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 K. V. Anokhin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K. V. Anokhin more than expected).
Fields of papers citing papers by K. V. Anokhin
This network shows the impact of papers produced by K. V. Anokhin. 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 K. V. Anokhin. The network helps show where K. V. Anokhin may publish in the future.
Co-authorship network of co-authors of K. V. Anokhin
This figure shows the co-authorship network connecting the top 25 collaborators of K. V. Anokhin. A scholar is included among the top collaborators of K. V. Anokhin 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 K. V. Anokhin. K. V. Anokhin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 45 | |
| 9 | 20 | |
| 10 | 6 | |
| 11 | 2 | |
| 12 | A new design for a green calcium indicator with a smaller size and a reduced number of calcium-binding sites | 1 |
| 13 | Automatic segmentation of mouse behavior using hidden Markov model | 1 |
| 14 | 77 | |
| 15 | 3 | |
| 16 | 37 | |
| 17 | 3 | |
| 18 | 3 | |
| 19 | Learning drives the accumulation of adaptive complexity in simulated evolution. | 0 |
| 20 | 31 |
About K. V. Anokhin
K. V. Anokhin is a scholar working on Biophysics, Cellular and Molecular Neuroscience and Behavioral Neuroscience, having authored 136 papers that have together received 2.0k indexed citations. Recurring topics across this work include Memory and Neural Mechanisms (37 papers), Neuroscience and Neuropharmacology Research (31 papers) and Photoreceptor and optogenetics research (28 papers). The work is most often cited by research in Biophysics (307 citations), Cellular and Molecular Neuroscience (727 citations) and Behavioral Neuroscience (124 citations). K. V. Anokhin has collaborated with scholars based in Russia, United States and United Kingdom. Frequent co-authors include Steven P. R. Rose, А. А. Тиунова, А. М. Желтиков, О. И. Ивашкина, A. B. Fedotov, Lyubov V. Amitonova, И. В. Федотов, Ilya V. Fedotov, Fedor V. Subach and Oleg Dolgov. Their work appears in journals such as Nature, The Lancet and Nucleic Acids Research.
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.