Mikhail Paveliev

543 total citations
19 papers, 429 citations indexed

About

Mikhail Paveliev is a scholar working on Cellular and Molecular Neuroscience, Cell Biology and Molecular Biology. According to data from OpenAlex, Mikhail Paveliev has authored 19 papers receiving a total of 429 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cellular and Molecular Neuroscience, 10 papers in Cell Biology and 7 papers in Molecular Biology. Recurrent topics in Mikhail Paveliev's work include Nerve injury and regeneration (10 papers), Proteoglycans and glycosaminoglycans research (9 papers) and Glycosylation and Glycoproteins Research (4 papers). Mikhail Paveliev is often cited by papers focused on Nerve injury and regeneration (10 papers), Proteoglycans and glycosaminoglycans research (9 papers) and Glycosylation and Glycoproteins Research (4 papers). Mikhail Paveliev collaborates with scholars based in Finland, Russia and Austria. Mikhail Paveliev's co-authors include Märt Saarma, Heikki Rauvala, Maxim M. Bespalov, Yulia Sidorova, Evgeny Kulesskiy, Sarka Tumova, Claudio Rivera, Natalia Kulesskaya, Matti S. Airaksinen and Juha Kuja‐Panula and has published in prestigious journals such as The Journal of Cell Biology, Scientific Reports and Brain Research.

In The Last Decade

Mikhail Paveliev

18 papers receiving 419 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mikhail Paveliev Finland 10 267 153 135 92 46 19 429
Telma E. Santos Portugal 8 251 0.9× 163 1.1× 129 1.0× 140 1.5× 24 0.5× 8 439
Erna A. van Niekerk United States 7 236 0.9× 319 2.1× 94 0.7× 91 1.0× 24 0.5× 9 518
Michèle Carnaud France 11 299 1.1× 319 2.1× 194 1.4× 93 1.0× 37 0.8× 11 624
Chin Lik Tan United Kingdom 10 307 1.1× 251 1.6× 217 1.6× 102 1.1× 67 1.5× 14 605
Pavol Zelina France 11 276 1.0× 246 1.6× 111 0.8× 143 1.6× 40 0.9× 14 485
Jiefei Yang United States 5 269 1.0× 268 1.8× 80 0.6× 76 0.8× 60 1.3× 7 434
Elena Sopova Sweden 7 125 0.5× 214 1.4× 99 0.7× 59 0.6× 37 0.8× 11 354
Richard Eva United Kingdom 14 316 1.2× 288 1.9× 221 1.6× 175 1.9× 20 0.4× 19 584
Mirela Spillane United States 7 345 1.3× 392 2.6× 243 1.8× 136 1.5× 32 0.7× 8 677
Michael Karus Germany 8 137 0.5× 215 1.4× 102 0.8× 138 1.5× 19 0.4× 9 425

Countries citing papers authored by Mikhail Paveliev

Since Specialization
Citations

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

Fields of papers citing papers by Mikhail Paveliev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mikhail Paveliev

This figure shows the co-authorship network connecting the top 25 collaborators of Mikhail Paveliev. A scholar is included among the top collaborators of Mikhail Paveliev 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 Mikhail Paveliev. Mikhail Paveliev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Paveliev, Mikhail, et al.. (2025). Neuroimplants and the Glial Scar: What Makes the Brain–Computer Link Work?. Journal of Neurochemistry. 169(9). e70203–e70203.
2.
Paveliev, Mikhail, et al.. (2024). Perineuronal Net Microscopy: From Brain Pathology to Artificial Intelligence. International Journal of Molecular Sciences. 25(8). 4227–4227. 3 indexed citations
3.
Андрианов, В. В., et al.. (2023). Investigation of NO Role in Neural Tissue in Brain and Spinal Cord Injury. Molecules. 28(21). 7359–7359. 1 indexed citations
4.
Аганов, А. В., et al.. (2022). Postnatal development of the microstructure of cortical GABAergic synapses and perineuronal nets requires sensory input. Neuroscience Research. 182. 32–40. 2 indexed citations
5.
Kulesskaya, Natalia, Rimante Minkeviciene, Natalia Acosta‐Baena, et al.. (2022). Low-Molecular Weight Protamine Overcomes Chondroitin Sulfate Inhibition of Neural Regeneration. Frontiers in Cell and Developmental Biology. 10. 865275–865275. 7 indexed citations
6.
7.
Kaushik, Rahul, et al.. (2020). Fine structure analysis of perineuronal nets in the ketamine model of schizophrenia. European Journal of Neuroscience. 53(12). 3988–4004. 28 indexed citations
8.
Jäälinoja, Harri, Alexander Zhigalov, Natalia Kulesskaya, et al.. (2019). Quantitative changes in perineuronal nets in development and posttraumatic condition. Journal of Molecular Histology. 50(3). 203–216. 20 indexed citations
9.
Rauvala, Heikki, Mikhail Paveliev, Juha Kuja‐Panula, & Natalia Kulesskaya. (2017). Inhibition and enhancement of neural regeneration by chondroitin sulfate proteoglycans. Neural Regeneration Research. 12(5). 687–687. 37 indexed citations
10.
Paveliev, Mikhail, Keith K. Fenrich, Mikhail Kislin, et al.. (2016). HB-GAM (pleiotrophin) reverses inhibition of neural regeneration by the CNS extracellular matrix. Scientific Reports. 6(1). 33916–33916. 41 indexed citations
11.
Uvarov, Pavel, et al.. (2016). Spatial patterns and cell surface clusters in perineuronal nets. Brain Research. 1648(Pt A). 214–223. 13 indexed citations
12.
Paveliev, Mikhail, Mikhail Kislin, Dmitry Molotkov, et al.. (2014). Acute Brain Trauma in Mice Followed By Longitudinal Two-photon Imaging. Journal of Visualized Experiments. 1 indexed citations
13.
Paveliev, Mikhail, Mikhail Kislin, Dmitry Molotkov, et al.. (2014). Acute Brain Trauma in Mice Followed By Longitudinal Two-photon Imaging. Journal of Visualized Experiments. 9 indexed citations
14.
Bespalov, Maxim M., Yulia Sidorova, Sarka Tumova, et al.. (2011). Heparan sulfate proteoglycan syndecan-3 is a novel receptor for GDNF, neurturin, and artemin. The Journal of Cell Biology. 192(1). 153–169. 163 indexed citations
15.
Sidorova, Yulia, Kert Mätlik, Mikhail Paveliev, et al.. (2010). Persephin signaling through GFRα1: The potential for the treatment of Parkinson's disease. Molecular and Cellular Neuroscience. 44(3). 223–232. 27 indexed citations
16.
Paveliev, Mikhail, Anni Hienola, Eija Jokitalo, et al.. (2008). Sensory neurons from N-syndecan-deficient mice are defective in survival. Neuroreport. 19(14). 1397–1400. 6 indexed citations
17.
Paveliev, Mikhail, et al.. (2007). Neurotrophic factors switch between two signaling pathways that trigger axonal growth. Journal of Cell Science. 120(15). 2507–2516. 14 indexed citations
18.
Paveliev, Mikhail, Matti S. Airaksinen, & Märt Saarma. (2004). GDNF family ligands activate multiple events during axonal growth in mature sensory neurons. Molecular and Cellular Neuroscience. 25(3). 453–459. 42 indexed citations
19.
Nevskaya, N., Svetlana Tishchenko, Mikhail Paveliev, et al.. (2002). Structure of ribosomal protein L1 fromMethanococcus thermolithotrophicus. Functionally important structural invariants on the L1 surface. Acta Crystallographica Section D Biological Crystallography. 58(6). 1023–1029. 12 indexed citations

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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