В. С. Кудрин

1.8k total citations
157 papers, 1.3k citations indexed

About

В. С. Кудрин is a scholar working on Cellular and Molecular Neuroscience, Physiology and Molecular Biology. According to data from OpenAlex, В. С. Кудрин has authored 157 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 85 papers in Cellular and Molecular Neuroscience, 53 papers in Physiology and 40 papers in Molecular Biology. Recurrent topics in В. С. Кудрин's work include Neuroscience and Neuropharmacology Research (63 papers), Neurotransmitter Receptor Influence on Behavior (39 papers) and Biochemical effects in animals (25 papers). В. С. Кудрин is often cited by papers focused on Neuroscience and Neuropharmacology Research (63 papers), Neurotransmitter Receptor Influence on Behavior (39 papers) and Biochemical effects in animals (25 papers). В. С. Кудрин collaborates with scholars based in Russia, United Kingdom and Finland. В. С. Кудрин's co-authors include Alexander V. Oleskin, В. Б. Наркевич, K.S. Rayevsky, Е. А. Цавкелова, M. V. Ugrumov, A. S. Bazyan, А. С. Штемберг, V. G. Kucheryanu, Е. А. Козина and K. Yu. Sarkisova and has published in prestigious journals such as SHILAP Revista de lepidopterología, Brain Research and International Journal of Molecular Sciences.

In The Last Decade

В. С. Кудрин

135 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
В. С. Кудрин Russia 17 574 461 381 203 195 157 1.3k
Rubén Antonio Vázquez‐Roque Mexico 21 387 0.7× 379 0.8× 373 1.0× 141 0.7× 138 0.7× 48 1.3k
Tatiana Melnikova United States 11 387 0.7× 439 1.0× 744 2.0× 157 0.8× 205 1.1× 16 1.6k
Musa V. Mabandla South Africa 19 239 0.4× 288 0.6× 182 0.5× 149 0.7× 224 1.1× 75 1.1k
Yukio Takamatsu Japan 15 365 0.6× 465 1.0× 214 0.6× 84 0.4× 115 0.6× 32 1.1k
Dubravka Švob Štrac Croatia 24 625 1.1× 529 1.1× 421 1.1× 383 1.9× 80 0.4× 95 1.9k
Cristina Cosi France 27 939 1.6× 1.1k 2.4× 223 0.6× 110 0.5× 168 0.9× 51 2.1k
Izuru Matsumoto Australia 29 892 1.6× 958 2.1× 278 0.7× 197 1.0× 196 1.0× 62 2.3k
Yanyan Guo China 25 682 1.2× 515 1.1× 391 1.0× 140 0.7× 72 0.4× 69 1.8k
David Dao United States 12 494 0.9× 409 0.9× 203 0.5× 304 1.5× 89 0.5× 27 1.5k
Xiao‐Ming Ou United States 27 789 1.4× 823 1.8× 188 0.5× 271 1.3× 245 1.3× 40 2.2k

Countries citing papers authored by В. С. Кудрин

Since Specialization
Citations

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

Fields of papers citing papers by В. С. Кудрин

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by В. С. Кудрин. 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 В. С. Кудрин. The network helps show where В. С. Кудрин may publish in the future.

Co-authorship network of co-authors of В. С. Кудрин

This figure shows the co-authorship network connecting the top 25 collaborators of В. С. Кудрин. A scholar is included among the top collaborators of В. С. Кудрин 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 В. С. Кудрин. В. С. Кудрин 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
1.
Yarullina, D. R., et al.. (2024). Probiotic Lactobacilli Ameliorate Antibiotic-Induced Cognitive and Behavioral Impairments in Mice. SHILAP Revista de lepidopterología. 15(3). 1471–1485. 3 indexed citations
2.
Наркевич, В. Б., et al.. (2023). Nine-month-long Social Isolation Changes the Levels of Monoamines in the Brain Structures of Rats: A Comparative Study of Neurochemistry and Behavior. Neurochemical Research. 48(6). 1755–1774. 3 indexed citations
3.
Sarkisova, K. Yu., et al.. (2023). Effects of Interferon-α on Depressive-Like Behavior and Brain Neurochemistry in Rats Housed in Standard and Overcrowding Conditions. Journal of Evolutionary Biochemistry and Physiology. 59(6). 2005–2021.
4.
Кудрин, В. С., et al.. (2023). Neurobiological Effects of Combined Exposure to Antiorthostatic Suspension, Quasi-Chronic Gamma Irradiation and Heavy Ion Irradiation in Rats. Российский физиологический журнал им  И  М  Сеченова. 109(3). 348–365.
5.
Воронина, Т. А., et al.. (2023). The Role of Brain Monoamines in the Formation of Audiogenic Myoclonic Seizures in Krushinsky–Molodkina Rats. Neurochemical Journal. 17(1). 84–90. 1 indexed citations
6.
7.
Кудрин, В. С., et al.. (2022). Correction of alcohol-induced disorders of working memory with noopept. 20(6). 56–64.
8.
Zolotarev, Yu. A., С. И. Шрам, О. В. Долотов, et al.. (2022). HLDF-6 peptides exhibit neuroprotective effects in the experimental model of preclinical Parkinson's disease. Neuropeptides. 96. 102287–102287. 2 indexed citations
9.
Васильева, Е. В., et al.. (2020). The effects of cycloprolylglycine and its analogues on brain monoaminergic systems in BALB/c mice. SHILAP Revista de lepidopterología. 3–10. 1 indexed citations
10.
11.
Наркевич, В. Б., et al.. (2019). Changes in Monoamine Levels in BALB/c and 57Bl/6N Mice in Response to Acute Stress with Different Controllability. Bulletin of Experimental Biology and Medicine. 167(5). 610–615. 3 indexed citations
12.
Soshnikova, Natalia V., А. Н. Краснов, Nadezhda E. Vorobyeva, et al.. (2018). Upgraded Methodology for the Development of Early Diagnosis of Parkinson’s Disease Based on Searching Blood Markers in Patients and Experimental Models. Molecular Neurobiology. 56(5). 3437–3450. 27 indexed citations
13.
Кудрин, В. С., et al.. (2018). An investigation of the single and combined effects of hypogravity and ionizing radiation on brain monoamine metabolism and rats’ behavior. Life Sciences in Space Research. 20. 12–19. 19 indexed citations
14.
15.
Sarkisova, K. Yu., et al.. (2015). Behavioral and Neurochemical Characteristics of Two Months Old WAG/Rij Rats with Genetic Absence Epilepsy. 3(2). 32–44. 6 indexed citations
16.
Gruden, M. A., et al.. (2014). Intranasal administration of alpha-synuclein aggregates: a Parkinson's disease model with behavioral and neurochemical correlates. Behavioural Brain Research. 263. 158–168. 17 indexed citations
17.
Кудрин, В. С., et al.. (2011). Changes in the Levels of Inhibitory and Excitatory Amino Acids in the Brain Structures of Female Rats with Cobalt Epileptogenic Focus during Different Phases of the Estrous Cycle. Bulletin of Experimental Biology and Medicine. 152(1). 47–49. 1 indexed citations
18.
Ugrumov, M. V., Е. А. Козина, V. G. Kucheryanu, et al.. (2011). Modeling of presymptomatic and symptomatic stages of parkinsonism in mice. Neuroscience. 181. 175–188. 102 indexed citations
19.
Melnikova, V. I., et al.. (2005). Dopamine Synthesis by Non-Dopaminergic Neurons in the Arcuate Nucleus of Rat Fetuses. Neuroscience and Behavioral Physiology. 35(8). 809–813. 4 indexed citations
20.
Bashkatova, V. G., et al.. (1995). Transmitter amino acids, lipid peroxidation and antioxidant defenсe mechanisms in the brain of rats with audiogenic epilepsy. Journal of Neurochemistry. 65. 191–198. 1 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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