A.I. Archakov

443 citations
45 papers · 370 · h-index 11

Impact in

    • Pharmacogenetics and Drug Metabolism
  • Spectroscopy top 10%
    • Analytical Chemistry and Chromatography
    • Advanced Proteomics Techniques and Applications

Papers in

A.I. Archakov

43 papers receiving 362 citations

Peers

A.I. Archakov
Comparison fields: 5 of 82
  • Pharmacology 138
  • Spectroscopy 73
  • Electrochemistry 24
  • Toxicology 13
  • Computational Theory and Mathematics 56
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H Graf Germany
Heinrich Meier Germany
Chuanwu Xia United States
Satya Prakash Panda United States
Bruno Cerra Italy
Sarah C. Traeger United States
Vı́ctor Segarra Spain
Shanthi Govindaraj United States
Kirk L. Stevens United States
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Citations per field
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Citations per year

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-authors

The 25 scholars most cited alongside A.I. Archakov, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with A.I. Archakov Line = papers co-authored together A.I. Archakov links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199454
2 200640
3 199133
4 200924
5 199219
6 199413
7 201711
8 201511
9 201010
10 201010
11 201510
12 19868
13 19878
14 20158
15 19998
16 20137
17 20187
18 20226
19 19756
20 20116

About A.I. Archakov

A.I. Archakov is a scholar working on Molecular Biology, Pharmacology, Computational Theory and Mathematics, Spectroscopy and Oncology, having authored 45 papers that have together received 370 indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (15 papers), Computational Drug Discovery Methods (13 papers), Analytical Chemistry and Chromatography (5 papers), Metabolomics and Mass Spectrometry Studies (5 papers), Electrochemical sensors and biosensors (4 papers), Drug Transport and Resistance Mechanisms (4 papers), Innovative Microfluidic and Catalytic Techniques Innovation (3 papers) and Electrochemical Analysis and Applications (3 papers). The work is most often cited by research in Pharmacology (138 citations), Spectroscopy (73 citations), Electrochemistry (24 citations), Toxicology (13 citations) and Computational Theory and Mathematics (56 citations). A.I. Archakov has collaborated with scholars based in Russia, Belarus and Germany. Frequent co-authors include G.I. Bachmanova, Victoria V. Shumyantseva, Tatiana V. Bulko, Žilvinas Anusevičius, Daiva Bironaitė, Karin Öllinger, Irina P. Kanaeva, Alexey V. Kuzikov, Г.П. Кузнецова and O. Ristau. Their work appears in journals such as Archives of Biochemistry and Biophysics, Xenobiotica, Biochemical and Biophysical Research Communications, Russian Chemical Reviews and IUBMB Life.

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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