Д. А. Михайлов

2.1k citations
49 papers · 1.5k indexed · 1 hit paper · h-index 17

Impact in

Papers in

Д. А. Михайлов

42 papers receiving 1.5k citations

Hit Papers

Large-scale prediction and testing of drug activity on side-effect targets 2012 · 656 citations
6562012202620162021200400600

Peers

Д. А. Михайлов
Comparison fields: 5 of 126
  • Computational Theory and Mathematics 817
  • Pharmacology 220
  • Toxicology 67
  • Molecular Biology 888
  • Pharmacology 209
Replace Xueliang Fang with:
Xueliang Fang China
H. C. Stephen Chan China
Allison K. Doak United States
Hongmao Sun United States
Adam Yasgar United States
Matthias Wirth Germany
Peichen Pan China
Alexander Hillisch Germany
Olivier Spérandio France
Elena Cibrián–Uhalte Germany
Д. А. Михайлов relative to Xueliang Fang China Xueliang Fang's profile →
Citations per field
00.5×1.5×2.4×
Xueliang Fang · 1×
Citations per year

Countries citing papers authored by Д. А. Михайлов

Since Specialization
Citations

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

Fields of papers citing papers by Д. А. Михайлов

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Д. А. Михайлов. 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 Д. А. Михайлов. The network helps show where Д. А. Михайлов may publish in the future.

Co-authors

The 25 scholars most cited alongside Д. А. Михайлов, 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 Д. А. Михайлов Line = papers co-authored together Д. А. Михайлов links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20232
3 20211
4 20214
5 20201
6 201910
7 20191
8 20193
9 201336
10
Large-scale prediction and testing of drug activity on side-effect targets
Hit paper breakdown →
2012656
11 20117
12 201014
13 20105
14 200958
15 20091
16 200770
17 20041
18 199965
19 199722
20 199643

About Д. А. Михайлов

Д. А. Михайлов is a scholar working on Algebra and Number Theory, Discrete Mathematics and Combinatorics, Computational Theory and Mathematics, Ceramics and Composites and Spectroscopy, having authored 49 papers that have together received 1.5k indexed citations. Recurring topics across this work include Nuclear materials and radiation effects (8 papers), Computational Drug Discovery Methods (7 papers), Spectroscopy and Laser Applications (7 papers), Semiconductor Lasers and Optical Devices (5 papers), Laser Design and Applications (5 papers), Biosimilars and Bioanalytical Methods (4 papers), Luminescence Properties of Advanced Materials (4 papers) and Proteoglycans and glycosaminoglycans research (4 papers). The work is most often cited by research in Computational Theory and Mathematics (817 citations), Pharmacology (220 citations), Toxicology (67 citations), Molecular Biology (888 citations) and Pharmacology (209 citations). Д. А. Михайлов has collaborated with scholars based in Russia, United States and Switzerland. Frequent co-authors include Jeremy L. Jenkins, László Urbán, Steven Whitebread, Jacques Hamon, Eugen Lounkine, Michael J. Keiser, Brian K. Shoichet, Eckhard Weber, Serge Côté and Allison K. Doak. Their work appears in journals such as Biochemical Journal, Bioanalysis, Ceramics International, Journal of Proteome Research and Nature.

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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