Igor Popov

3.2k total citations
180 papers, 2.5k citations indexed

About

Igor Popov is a scholar working on Spectroscopy, Molecular Biology and Physiology. According to data from OpenAlex, Igor Popov has authored 180 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 93 papers in Spectroscopy, 78 papers in Molecular Biology and 30 papers in Physiology. Recurrent topics in Igor Popov's work include Mass Spectrometry Techniques and Applications (79 papers), Metabolomics and Mass Spectrometry Studies (46 papers) and Advanced Proteomics Techniques and Applications (34 papers). Igor Popov is often cited by papers focused on Mass Spectrometry Techniques and Applications (79 papers), Metabolomics and Mass Spectrometry Studies (46 papers) and Advanced Proteomics Techniques and Applications (34 papers). Igor Popov collaborates with scholars based in Russia, United States and Canada. Igor Popov's co-authors include Е. Н. Николаев, А. С. Кононихин, Yury Kostyukevich, Irina V. Perminova, Maria I. Indeykina, Sergey A. Kozin, Alexander Makarov, Alexander Zherebker, Natalia Starodubtseva and Oleg N. Kharybin and has published in prestigious journals such as Environmental Science & Technology, The Journal of Immunology and PLoS ONE.

In The Last Decade

Igor Popov

173 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Igor Popov Russia 29 951 890 366 302 255 180 2.5k
А. С. Кононихин Russia 29 836 0.9× 940 1.1× 378 1.0× 401 1.3× 268 1.1× 238 2.8k
Péter Horvatovich Netherlands 32 833 0.9× 1.8k 2.0× 159 0.4× 353 1.2× 139 0.5× 131 3.5k
Wolfram Gronwald Germany 31 526 0.6× 2.0k 2.2× 176 0.5× 200 0.7× 128 0.5× 101 3.2k
Michael A. Freitas United States 39 1.5k 1.5× 3.0k 3.4× 183 0.5× 214 0.7× 270 1.1× 133 4.9k
Michael Guilhaus Australia 33 1.3k 1.4× 1.4k 1.6× 272 0.7× 265 0.9× 407 1.6× 83 3.4k
Emílio Marengo Italy 30 397 0.4× 1.2k 1.3× 172 0.5× 292 1.0× 357 1.4× 141 2.8k
Hui Ye China 30 796 0.8× 1.6k 1.8× 156 0.4× 216 0.7× 51 0.2× 120 2.9k
Marc Roth Switzerland 24 568 0.6× 1.7k 1.9× 346 0.9× 465 1.5× 200 0.8× 67 3.6k
Christian Ludwig United Kingdom 33 482 0.5× 2.0k 2.3× 226 0.6× 196 0.6× 113 0.4× 126 3.7k
Raf Van de Plas United States 22 980 1.0× 1.2k 1.3× 62 0.2× 178 0.6× 175 0.7× 48 2.3k

Countries citing papers authored by Igor Popov

Since Specialization
Citations

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

Fields of papers citing papers by Igor Popov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Igor Popov

This figure shows the co-authorship network connecting the top 25 collaborators of Igor Popov. A scholar is included among the top collaborators of Igor Popov 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 Igor Popov. Igor Popov 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.
Sorokin, Anatoly, et al.. (2024). Modern machine‐learning applications in ambient ionization mass spectrometry. Mass Spectrometry Reviews. 44(1). 74–88. 7 indexed citations
2.
Sorokin, Anatoly, et al.. (2023). Shapley Value as a Quality Control for Mass Spectra of Human Glioblastoma Tissues. Data. 8(1). 21–21. 1 indexed citations
3.
4.
Popov, Igor, et al.. (2022). Ambient ms profiling of meningiomas: intraoperative oncometabolite-based monitoring. Bulletin of Russian State Medical University. 74–81. 1 indexed citations
5.
Ларина, И. М., et al.. (2022). The lightweight spherical samplers for simplified collection, storage, and ambient ionization of drugs from saliva and blood. Acta Astronautica. 195. 556–560. 3 indexed citations
6.
Sorokin, Anatoly, et al.. (2021). Lipid Profiles of Human Brain Tumors Obtained by High-Resolution Negative Mode Ambient Mass Spectrometry. Data. 6(12). 132–132. 4 indexed citations
7.
Popov, Igor, et al.. (2021). Echolocation of bats (Chiroptera Blumenbach, 1779) as an element of their ecological plasticity. South of Russia ecology development. 15(4). 6–20. 4 indexed citations
8.
Кононихин, А. С., Anna E. Bugrova, Maria I. Indeykina, et al.. (2018). Methodology for Urine Peptidome Analysis Based on Nano-HPLC Coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry. Methods in molecular biology. 1719. 311–318. 2 indexed citations
9.
Kostyukevich, Yury, et al.. (2017). CID fragmentation, H/D exchange and supermetallization of Barnase-Barstar complex. Scientific Reports. 7(1). 6176–6176. 3 indexed citations
10.
Кононихин, А. С., et al.. (2016). Proteomic analysis of exhaled breath condensate for diagnostics of respiratory system diseases. Biochemistry (Moscow) Supplement Series B Biomedical Chemistry. 10(3). 230–234. 3 indexed citations
11.
Кононихин, А. С., et al.. (2016). Early diagnosis of lung cancer based on proteome analysis of exhaled breath condensate. Moscow University Chemistry Bulletin. 71(2). 134–139. 8 indexed citations
12.
Кононихин, А. С., Natalia Starodubtseva, А. Е. Бугрова, et al.. (2016). An untargeted approach for the analysis of the urine peptidome of women with preeclampsia. Journal of Proteomics. 149. 38–43. 33 indexed citations
13.
Kulikova, Alexandra A., Philipp O. Tsvetkov, Maria I. Indeykina, et al.. (2014). Phosphorylation of Ser8 promotes zinc-induced dimerization of the amyloid-β metal-binding domain. Molecular BioSystems. 10(10). 2590–2596. 46 indexed citations
14.
Кононихин, А. С., et al.. (2014). COMPARATIVE PROTEOMIC ANALYSIS OF EXHALED BREATH CONDENSATE IN PATIENTS WITH LUNG CARCINOMA USING HIGH RESOLUTION MASS-SPECTROMETRY. PULMONOLOGIYA. 5–11. 7 indexed citations
15.
Feldman, T. B., M. A. Yakovleva, А. С. Кононихин, et al.. (2014). Changes in spectral properties and composition of lipofuscin fluorophores from human-retinal-pigment epithelium with age and pathology. Analytical and Bioanalytical Chemistry. 407(4). 1075–1088. 33 indexed citations
16.
Лобанов, А. В., et al.. (2013). New step towards artificial photosynthesis: Photogeneration of organic compounds in the inorganic carbon-hydrogen peroxide-phthalocyanine system. Doklady Physical Chemistry. 453(2). 275–278. 1 indexed citations
17.
Ichim, Thomas E., Mu Li, Hua Qian, et al.. (2004). RNA Interference: A Potent Tool for Gene-Specific Therapeutics. American Journal of Transplantation. 4(8). 1227–1236. 79 indexed citations
18.
Popov, Igor, Charles S. Dela Cruz, Brian H. Barber, Basil Chiu, & Robert D. Inman. (2002). Breakdown of CTL Tolerance to Self HLA-B*2705 Induced by Exposure to Chlamydia   trachomatis. The Journal of Immunology. 169(7). 4033–4038. 20 indexed citations
19.
Popov, Igor, Charles S. Dela Cruz, Brian H. Barber, Basil Chiu, & Robert D. Inman. (2001). The Effect of an Anti-HLA-B27 Immune Response on CTL Recognition of Chlamydia. The Journal of Immunology. 167(6). 3375–3382. 15 indexed citations
20.
Popov, Igor. (1996). Structural modification of films of amorphous hydrogenated silicon using ultraviolet radiation. Semiconductors. 30(3). 258–261. 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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