Pavel Karpov

968 total citations
22 papers, 427 citations indexed

About

Pavel Karpov is a scholar working on Computational Theory and Mathematics, Molecular Biology and Organic Chemistry. According to data from OpenAlex, Pavel Karpov has authored 22 papers receiving a total of 427 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computational Theory and Mathematics, 7 papers in Molecular Biology and 6 papers in Organic Chemistry. Recurrent topics in Pavel Karpov's work include Computational Drug Discovery Methods (12 papers), Analytical Chemistry and Chromatography (4 papers) and Neural Networks and Applications (4 papers). Pavel Karpov is often cited by papers focused on Computational Drug Discovery Methods (12 papers), Analytical Chemistry and Chromatography (4 papers) and Neural Networks and Applications (4 papers). Pavel Karpov collaborates with scholars based in Russia, Germany and Tajikistan. Pavel Karpov's co-authors include Igor V. Tetko, Guillaume Godin, Věra Kůrková, Fabian J. Theis, Igor I. Baskin, Vladimir A. Palyulin, Maxim V. Fedorov, Sergey Sosnin, N. S. Zefirov and Н. С. Зефиров and has published in prestigious journals such as International Journal of Molecular Sciences, Bioorganic & Medicinal Chemistry Letters and Journal of Computer-Aided Molecular Design.

In The Last Decade

Pavel Karpov

22 papers receiving 419 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pavel Karpov Russia 10 247 165 145 76 45 22 427
Oliver Wieder Austria 6 311 1.3× 230 1.4× 190 1.3× 67 0.9× 40 0.9× 9 462
Stefan M. Kohlbacher Austria 6 250 1.0× 203 1.2× 162 1.1× 67 0.9× 34 0.8× 8 391
Arthur Garon Austria 9 370 1.5× 207 1.3× 280 1.9× 65 0.9× 64 1.4× 14 594
Kohulan Rajan Germany 11 314 1.3× 144 0.9× 347 2.4× 36 0.5× 46 1.0× 29 681
Zois Boukouvalas United States 10 309 1.3× 297 1.8× 198 1.4× 59 0.8× 16 0.4× 29 648
Ignacio Ponzoni Argentina 16 301 1.2× 131 0.8× 260 1.8× 103 1.4× 47 1.0× 54 687
Vishnu H Nair Switzerland 5 369 1.5× 463 2.8× 217 1.5× 111 1.5× 22 0.5× 5 659
Dávid Lányi Switzerland 5 210 0.9× 217 1.3× 126 0.9× 83 1.1× 13 0.3× 5 370
Sergey Sosnin Russia 12 289 1.2× 175 1.1× 225 1.6× 39 0.5× 21 0.5× 22 491
Simon Johansson Sweden 8 487 2.0× 404 2.4× 330 2.3× 59 0.8× 23 0.5× 19 678

Countries citing papers authored by Pavel Karpov

Since Specialization
Citations

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

Fields of papers citing papers by Pavel Karpov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pavel Karpov

This figure shows the co-authorship network connecting the top 25 collaborators of Pavel Karpov. A scholar is included among the top collaborators of Pavel Karpov 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 Pavel Karpov. Pavel Karpov 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.
Karpov, Pavel, et al.. (2022). What Features of Ligands Are Relevant to the Opening of Cryptic Pockets in Drug Targets?. Informatics. 9(1). 8–8. 2 indexed citations
2.
Semenyuta, Ivan, Vasyl Kovalishyn, Sergiy Rogalsky, et al.. (2021). Structure-Activity Relationship Modeling and Experimental Validation of the Imidazolium and Pyridinium Based Ionic Liquids as Potential Antibacterials of MDR Acinetobacter baumannii and Staphylococcus aureus. International Journal of Molecular Sciences. 22(2). 563–563. 14 indexed citations
3.
Li, Xueyao, Pavel Karpov, Hongwei Jin, et al.. (2021). Anti-MRSA drug discovery by ligand-based virtual screening and biological evaluation. Bioorganic Chemistry. 114. 105042–105042. 9 indexed citations
4.
Karpov, Pavel, Guillaume Godin, & Igor V. Tetko. (2020). Transformer-CNN: Swiss knife for QSAR modeling and interpretation. Journal of Cheminformatics. 12(1). 17–17. 170 indexed citations
5.
Karpov, Pavel, et al.. (2019). Focused Library Generator: case of Mdmx inhibitors. Journal of Computer-Aided Molecular Design. 34(7). 769–782. 8 indexed citations
6.
Tetko, Igor V., Věra Kůrková, Pavel Karpov, & Fabian J. Theis. (2019). Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part II. 8 indexed citations
7.
8.
Tetko, Igor V., et al.. (2019). Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series. Lecture notes in computer science. 27 indexed citations
9.
Tetko, Igor V., et al.. (2019). Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing. Lecture notes in computer science. 8 indexed citations
10.
Tetko, Igor V., et al.. (2019). Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions. Lecture notes in computer science. 29 indexed citations
11.
Sosnin, Sergey, et al.. (2018). A Survey of Multi‐task Learning Methods in Chemoinformatics. Molecular Informatics. 38(4). e1800108–e1800108. 63 indexed citations
12.
Ryzhkov, Fedor V., et al.. (2015). Molecular design of selective ligands of chemokine receptors. Doklady Biochemistry and Biophysics. 461(1). 131–134. 1 indexed citations
13.
Karpov, Pavel, et al.. (2011). Prediction of rate constants of S N 2 reactions by the multicomponent QSPR method. Doklady Chemistry. 440(2). 299–301. 12 indexed citations
14.
15.
Karpov, Pavel, Dmitry I. Osolodkin, Igor I. Baskin, Vladimir A. Palyulin, & Н. С. Зефиров. (2011). One-class classification as a novel method of ligand-based virtual screening: The case of glycogen synthase kinase 3β inhibitors. Bioorganic & Medicinal Chemistry Letters. 21(22). 6728–6731. 17 indexed citations
16.
17.
Karpov, Pavel, et al.. (2011). Method of continuous molecular fields in the one-class classification task. Doklady Chemistry. 440(2). 263–265. 6 indexed citations
18.
Karpov, Pavel, Igor I. Baskin, Vladimir A. Palyulin, & N. S. Zefirov. (2011). Virtual screening based on one-class classification. Doklady Chemistry. 437(2). 107–111. 6 indexed citations
19.
Karpov, Pavel, et al.. (2010). Neural network modeling of substituent constants on the basis of fragmental descriptors. Doklady Chemistry. 431(1). 85–88. 1 indexed citations
20.
Karpov, Pavel, et al.. (2007). “Bimolecular” QSPR: Estimation of the solvation free energy of organic molecules in different solvents. Doklady Chemistry. 414(1). 128–131. 11 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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