A. I. Archakov

1.0k total citations
54 papers, 839 citations indexed

About

A. I. Archakov is a scholar working on Molecular Biology, Spectroscopy and Pharmacology. According to data from OpenAlex, A. I. Archakov has authored 54 papers receiving a total of 839 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 23 papers in Spectroscopy and 14 papers in Pharmacology. Recurrent topics in A. I. Archakov's work include Metabolomics and Mass Spectrometry Studies (18 papers), Pharmacogenetics and Drug Metabolism (14 papers) and Mass Spectrometry Techniques and Applications (13 papers). A. I. Archakov is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (18 papers), Pharmacogenetics and Drug Metabolism (14 papers) and Mass Spectrometry Techniques and Applications (13 papers). A. I. Archakov collaborates with scholars based in Russia, United Kingdom and Sweden. A. I. Archakov's co-authors include Petr G. Lokhov, Kirill Degtyarenko, Victoria V. Shumyantseva, Oleg N. Kharybin, Tatiana V. Bulko, Victor G. Zgoda, Oxana P. Trifonova, N. A. Petushkova, Sergei A. Moshkovskii and I. I. Karuzina and has published in prestigious journals such as SHILAP Revista de lepidopterología, Biochemical and Biophysical Research Communications and FEBS Letters.

In The Last Decade

A. I. Archakov

51 papers receiving 820 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A. I. Archakov Russia 19 473 202 179 90 90 54 839
I. I. Karuzina Russia 14 298 0.6× 189 0.9× 98 0.5× 61 0.7× 80 0.9× 51 542
David L. Roberts United States 6 591 1.2× 261 1.3× 72 0.4× 63 0.7× 49 0.5× 7 907
Ivanov As Russia 22 944 2.0× 209 1.0× 138 0.8× 259 2.9× 144 1.6× 183 1.8k
Martin Klvaňa Czechia 9 1.2k 2.5× 115 0.6× 119 0.7× 135 1.5× 53 0.6× 14 1.6k
Thomas M. Shea United States 11 537 1.1× 273 1.4× 83 0.5× 65 0.7× 61 0.7× 16 1.1k
Rosemary Paschke United States 9 979 2.1× 344 1.7× 94 0.5× 73 0.8× 63 0.7× 10 1.5k
Petr Medek Czechia 4 802 1.7× 81 0.4× 94 0.5× 111 1.2× 45 0.5× 8 1.1k
Scott Fountain United States 12 442 0.9× 43 0.2× 249 1.4× 42 0.5× 50 0.6× 18 1.0k
Vilém Šustr Czechia 3 862 1.8× 85 0.4× 95 0.5× 115 1.3× 45 0.5× 6 1.2k
D.A. Lysek United Kingdom 11 1.1k 2.3× 472 2.3× 89 0.5× 109 1.2× 25 0.3× 14 1.4k

Countries citing papers authored by A. I. Archakov

Since Specialization
Citations

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

Fields of papers citing papers by A. I. Archakov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. I. Archakov. 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 A. I. Archakov. The network helps show where A. I. Archakov may publish in the future.

Co-authorship network of co-authors of A. I. Archakov

This figure shows the co-authorship network connecting the top 25 collaborators of A. I. Archakov. A scholar is included among the top collaborators of A. I. Archakov 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 A. I. Archakov. A. I. Archakov 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.
Ponomarenko, Elena A., Yuri D. Ivanov, Tatyana O. Pleshakova, et al.. (2024). From Proteomics to the Analysis of Single Protein Molecules. International Journal of Molecular Sciences. 25(19). 10308–10308.
2.
Kaysheva, Anna L., Arthur T. Kopylov, Н. Е. Кушлинский, et al.. (2019). Comparative Analysis of Blood Plasma Proteome in Patients with Renal Cell Carcinoma. Bulletin of Experimental Biology and Medicine. 167(1). 91–96. 4 indexed citations
3.
Naryzhny, Stanislav, et al.. (2018). Next Steps on in Silico 2DE Analyses of Chromosome 18 Proteoforms. Journal of Proteome Research. 17(12). 4085–4096. 2 indexed citations
4.
Kaysheva, Anna L., Arthur T. Kopylov, Tatyana O. Pleshakova, et al.. (2017). Proteomic analysis of serum proteins of children with autism. SHILAP Revista de lepidopterología. 3 indexed citations
5.
Lokhov, Petr G., et al.. (2017). Label-free data standardization for clinical metabolomics. BioData Mining. 10(1). 10–10. 11 indexed citations
6.
Radko, Sergey P., et al.. (2016). Droplet digital PCR, a prospective technological approach to quantitative profiling of microRNA. Biochemistry (Moscow) Supplement Series B Biomedical Chemistry. 10(1). 22–30.
7.
Radko, Sergey P., et al.. (2016). Digital droplet PCR - a prospective technological approach to quantitative profiling of microRNA. Biomeditsinskaya Khimiya. 62(4). 403–410. 6 indexed citations
8.
Suprun, Elena V., Anatoly A. Saveliev, Gennady Evtugyn, et al.. (2012). Electrochemical approach for acute myocardial infarction diagnosis based on direct antibodies-free analysis of human blood plasma. Biosensors and Bioelectronics. 33(1). 158–164. 18 indexed citations
9.
Shumyantseva, Victoria V., et al.. (2010). Electrochemical investigations of cytochrome P450. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1814(1). 94–101. 38 indexed citations
10.
Zgoda, Victor G., Sergei A. Moshkovskii, Elena A. Ponomarenko, et al.. (2009). Proteomics of mouse liver microsomes: Performance of different protein separation workflows for LC‐MS/MS. PROTEOMICS. 9(16). 4102–4105. 23 indexed citations
11.
Moshkovskii, Sergei A., et al.. (2009). Cancer-specific MALDI-TOF profiles of blood serum and plasma: Biological meaning and perspectives. Journal of Proteomics. 73(3). 537–551. 48 indexed citations
12.
Shumyantseva, Victoria V., et al.. (2008). Stoichiometry of electrocatalytic cycle of cytochrome P450 2B4. Journal of Inorganic Biochemistry. 102(11). 2020–2025. 22 indexed citations
13.
Коплик, Е. В., et al.. (2008). Mass spectrometric profile of the serum as a marker of experimental psychoemotional stress in rats. Bulletin of Experimental Biology and Medicine. 145(5). 552–555.
14.
Kanaeva, Irina P., N. A. Petushkova, Andrey Lisitsa, et al.. (2005). Proteomic and biochemical analysis of the mouse liver microsomes. Toxicology in Vitro. 19(6). 805–812. 20 indexed citations
15.
Shumyantseva, Victoria V., et al.. (2003). Fluorescent assay for riboflavin binding to cytochrome P450 2B4. Journal of Inorganic Biochemistry. 98(2). 365–370. 28 indexed citations
16.
Archakov, A. I., I. I. Karuzina, N. A. Petushkova, А.В. Лисица, & Victor G. Zgoda. (2002). Production of carbon monoxide by cytochrome P450 during iron-dependent lipid peroxidation. Toxicology in Vitro. 16(1). 1–10. 20 indexed citations
17.
Shumyantseva, Victoria V., et al.. (1998). Semisynthetic Flavocytochromes Based on Cytochrome P450 2B4: Reductase and Oxygenase Activities. Archives of Biochemistry and Biophysics. 354(1). 133–138. 20 indexed citations
18.
Archakov, A. I., В. Г. Згода, & I. I. Karuzina. (1998). [Oxidative modification of cytochrome P450 and other macromolecules during its turnover].. PubMed. 44(1). 3–27. 5 indexed citations
19.
Degtyarenko, Kirill & A. I. Archakov. (1993). Molecular evolution of P450 superfamily and P450‐containing monooxygenase systems. FEBS Letters. 332(1-2). 1–8. 91 indexed citations
20.
Archakov, A. I., et al.. (1989). Инактивация цитохрома P-450 перекисью водорода, образующейся в каталитическом цикле при распаде пероксикомплекса.. Biochemistry (Moscow). 54(7). 1102–1107. 2 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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