Olga V. Tikhonova

1.2k total citations
80 papers, 803 citations indexed

About

Olga V. Tikhonova is a scholar working on Molecular Biology, Spectroscopy and Cell Biology. According to data from OpenAlex, Olga V. Tikhonova has authored 80 papers receiving a total of 803 indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Molecular Biology, 21 papers in Spectroscopy and 8 papers in Cell Biology. Recurrent topics in Olga V. Tikhonova's work include Advanced Proteomics Techniques and Applications (20 papers), Mass Spectrometry Techniques and Applications (9 papers) and Metabolomics and Mass Spectrometry Studies (8 papers). Olga V. Tikhonova is often cited by papers focused on Advanced Proteomics Techniques and Applications (20 papers), Mass Spectrometry Techniques and Applications (9 papers) and Metabolomics and Mass Spectrometry Studies (8 papers). Olga V. Tikhonova collaborates with scholars based in Russia, United Kingdom and Taiwan. Olga V. Tikhonova's co-authors include Victor G. Zgoda, Alexander I. Archakov, Sergei A. Moshkovskii, Светлана Новикова, Eugene Goufman, Marina V. Serebryakova, Arthur T. Kopylov, A. E. Medvedev, О.А. Бунеева and Ivanov As and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Olga V. Tikhonova

77 papers receiving 784 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Olga V. Tikhonova Russia 17 473 190 76 73 63 80 803
Mikhail A. Pyatnitskiy Russia 16 537 1.1× 160 0.8× 70 0.9× 45 0.6× 69 1.1× 48 875
Xiao‐Xia Shao China 20 759 1.6× 156 0.8× 71 0.9× 98 1.3× 60 1.0× 84 1.4k
Matthew J. McKay Australia 23 606 1.3× 292 1.5× 83 1.1× 91 1.2× 56 0.9× 55 1.2k
Heiner Koch Germany 9 706 1.5× 451 2.4× 59 0.8× 73 1.0× 38 0.6× 14 1.0k
Laxmikanth Kollipara Germany 15 674 1.4× 191 1.0× 42 0.6× 135 1.8× 65 1.0× 40 982
Marlène Marcellin France 15 591 1.2× 333 1.8× 56 0.7× 80 1.1× 56 0.9× 25 1.0k
Stefanie Wortelkamp Germany 9 830 1.8× 328 1.7× 62 0.8× 135 1.8× 80 1.3× 11 1.2k
Meena Choi United States 14 815 1.7× 478 2.5× 95 1.3× 85 1.2× 57 0.9× 24 1.2k
Yasmin J. Asad United Kingdom 9 650 1.4× 75 0.4× 70 0.9× 94 1.3× 62 1.0× 14 867
Daniel Hirschberg Sweden 17 724 1.5× 177 0.9× 99 1.3× 112 1.5× 112 1.8× 21 1.1k

Countries citing papers authored by Olga V. Tikhonova

Since Specialization
Citations

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

Fields of papers citing papers by Olga V. Tikhonova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Olga V. Tikhonova. 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 Olga V. Tikhonova. The network helps show where Olga V. Tikhonova may publish in the future.

Co-authorship network of co-authors of Olga V. Tikhonova

This figure shows the co-authorship network connecting the top 25 collaborators of Olga V. Tikhonova. A scholar is included among the top collaborators of Olga V. Tikhonova 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 Olga V. Tikhonova. Olga V. Tikhonova 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.
Новикова, Светлана, et al.. (2025). Secretome and Proteome of Extracellular Vesicles Provide Protein Markers of Lung and Colorectal Cancer. International Journal of Molecular Sciences. 26(3). 1016–1016. 1 indexed citations
2.
Новикова, Светлана, et al.. (2023). System analysis of surface CD markers during the process of granulocytic differentiation. Biomeditsinskaya Khimiya. 69(6). 383–393. 1 indexed citations
3.
Onishchenko, Natalia, Anna Alekseeva, Ivan Boldyrev, et al.. (2023). Protein Corona Attenuates the Targeting of Antitumor Sialyl Lewis X-Decorated Liposomes to Vascular Endothelial Cells under Flow Conditions. Pharmaceutics. 15(6). 1754–1754. 2 indexed citations
4.
Громова, О. А., et al.. (2023). Nephroprotective peptides of Laennec® in the context of pharmacotherapy for nephro-hepato-metabolic disorders. SHILAP Revista de lepidopterología. 16(4). 570–586. 1 indexed citations
5.
Torshin, I. Yu., О. А. Громова, Olga V. Tikhonova, & А. Г. Чучалин. (2023). Molecular mechanisms of the effect of standardized placental hydrolysate peptides on mitochondria functioning. Terapevticheskii arkhiv. 95(12). 1133–1140. 4 indexed citations
6.
Alekseeva, Anna, Ivan Boldyrev, С. В. Хайдуков, et al.. (2023). Protein Corona of Anionic Fluid-Phase Liposomes Compromises Their Integrity Rather than Uptake by Cells. Membranes. 13(7). 681–681. 6 indexed citations
7.
8.
Fedulova, Liliya, et al.. (2022). Proteomic Markers in the Muscles and Brain of Pigs Recovered from Hemorrhagic Stroke. Genes. 13(12). 2204–2204. 3 indexed citations
9.
10.
Archakov, Alexander I., Ekaterina V. Ilgisonis, Andrey Lisitsa, et al.. (2022). Number of Detected Proteins as the Function of the Sensitivity of ProteomicTechnology in Human Liver Cells. Current Protein and Peptide Science. 23(4). 290–298. 6 indexed citations
11.
Torshin, I. Yu., О. А. Громова, Olga V. Tikhonova, & Victor G. Zgoda. (2022). Hepatoprotective peptides of the drug Laennec. Experimental and Clinical Gastroenterology. 21–30. 7 indexed citations
12.
Kim, Yan, Daria M. Potashnikova, И. В. Холоденко, et al.. (2022). TRIM28 Is a Novel Regulator of CD133 Expression Associated with Cancer Stem Cell Phenotype. International Journal of Molecular Sciences. 23(17). 9874–9874. 8 indexed citations
13.
Kozlov, Konstantin, et al.. (2022). Quality Control of Human Pluripotent Stem Cell Colonies by Computational Image Analysis Using Convolutional Neural Networks. International Journal of Molecular Sciences. 24(1). 140–140. 6 indexed citations
14.
Русанов, А. Л., П. М. Кожин, Olga V. Tikhonova, et al.. (2021). Proteome Profiling of PMJ2-R and Primary Peritoneal Macrophages. International Journal of Molecular Sciences. 22(12). 6323–6323. 8 indexed citations
15.
Громова, О. А., et al.. (2021). Peptides contained in the composition of Laennec that contribute to the treatment of hyperferritinemia and iron overload disorders. SHILAP Revista de lepidopterología. 13(4). 413–425. 10 indexed citations
16.
Новикова, Светлана, Olga V. Tikhonova, Leonid K. Kurbatov, et al.. (2021). Omics Technologies to Decipher Regulatory Networks in Granulocytic Cell Differentiation. Biomolecules. 11(6). 907–907. 6 indexed citations
17.
Ушакова, Н. А., et al.. (2021). Novel Extract from Beetle Ulomoides dermestoides: A Study of Composition and Antioxidant Activity. Antioxidants. 10(7). 1055–1055. 13 indexed citations
18.
Medvedev, A. E., Arthur T. Kopylov, О.А. Бунеева, et al.. (2020). A Neuroprotective Dose of Isatin Causes Multilevel Changes Involving the Brain Proteome: Prospects for Further Research. International Journal of Molecular Sciences. 21(11). 4187–4187. 23 indexed citations
19.
Maltseva, D. V., E. N. Knyazev, Victor G. Zgoda, et al.. (2020). Knockdown of the α5 laminin chain affects differentiation of colorectal cancer cells and their sensitivity to chemotherapy. Biochimie. 174. 107–116. 23 indexed citations
20.
Moshkovskii, Sergei A., et al.. (2006). Acute phase serum amyloid A in ovarian cancer as an important component of proteome diagnostic profiling. PROTEOMICS - CLINICAL APPLICATIONS. 1(1). 107–117. 24 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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