Pavel Skums

3.2k total citations
64 papers, 743 citations indexed

About

Pavel Skums is a scholar working on Molecular Biology, Hepatology and Epidemiology. According to data from OpenAlex, Pavel Skums has authored 64 papers receiving a total of 743 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 22 papers in Hepatology and 20 papers in Epidemiology. Recurrent topics in Pavel Skums's work include Hepatitis C virus research (21 papers), Evolution and Genetic Dynamics (16 papers) and Genomics and Phylogenetic Studies (12 papers). Pavel Skums is often cited by papers focused on Hepatitis C virus research (21 papers), Evolution and Genetic Dynamics (16 papers) and Genomics and Phylogenetic Studies (12 papers). Pavel Skums collaborates with scholars based in United States, Russia and Belarus. Pavel Skums's co-authors include Alex Zelikovsky, Yury Khudyakov, Zoya Dimitrova, David S. Campo, Gilberto Vaughan, Joseph C. Forbi, Leonid Bunimovich, Sergey Knyazev, Lilia Ganova‐Raeva and Sumathi Ramachandran and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Pavel Skums

58 papers receiving 732 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 Skums United States 16 247 244 216 136 132 64 743
David S. Campo United States 15 189 0.8× 474 1.9× 497 2.3× 123 0.9× 122 0.9× 46 827
Pascal Mutz Germany 11 150 0.6× 365 1.5× 268 1.2× 248 1.8× 46 0.3× 20 713
Joshua B. Singer United Kingdom 15 156 0.6× 129 0.5× 94 0.4× 340 2.5× 52 0.4× 26 745
Kristof Theys Belgium 17 212 0.9× 180 0.7× 122 0.6× 515 3.8× 61 0.5× 55 829
Frederik Graw Germany 22 167 0.7× 339 1.4× 212 1.0× 328 2.4× 132 1.0× 54 1.1k
Ingo Bulla Germany 15 180 0.7× 162 0.7× 53 0.2× 270 2.0× 73 0.6× 32 912
Xuesen Zhao China 18 284 1.1× 628 2.6× 419 1.9× 801 5.9× 76 0.6× 30 1.5k
Ha Youn Lee United States 17 229 0.9× 204 0.8× 39 0.2× 332 2.4× 98 0.7× 38 880
Mengya Liu China 10 293 1.2× 162 0.7× 59 0.3× 408 3.0× 63 0.5× 25 888
Pieter Libin Belgium 16 147 0.6× 325 1.3× 145 0.7× 675 5.0× 36 0.3× 54 1.1k

Countries citing papers authored by Pavel Skums

Since Specialization
Citations

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

Fields of papers citing papers by Pavel Skums

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pavel Skums

This figure shows the co-authorship network connecting the top 25 collaborators of Pavel Skums. A scholar is included among the top collaborators of Pavel Skums 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 Skums. Pavel Skums 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.
2.
Bunimovich, Leonid & Pavel Skums. (2024). Fractal networks: Topology, dimension, and complexity. Chaos An Interdisciplinary Journal of Nonlinear Science. 34(4). 2 indexed citations
3.
Zelikovsky, Alex, et al.. (2024). Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks. Nature Communications. 15(1). 2838–2838. 3 indexed citations
4.
Yang, Chen, Yuriy Gankin, Gerardo Chowell, et al.. (2023). Excess mortality in Ukraine during the course of COVID-19 pandemic in 2020–2021. Scientific Reports. 13(1). 6917–6917. 5 indexed citations
5.
Bunimovich, Leonid, et al.. (2023). Antigenic cooperation in viral populations: Transformation of functions of intra-host viral variants. Journal of Theoretical Biology. 580. 111719–111719.
6.
Tariq, Amna, Tsira Chakhaia, Sushma Dahal, et al.. (2022). An investigation of spatial-temporal patterns and predictions of the coronavirus 2019 pandemic in Colombia, 2020–2021. PLoS neglected tropical diseases. 16(3). e0010228–e0010228. 8 indexed citations
7.
Vats, Kavita, Oleg Kruglov, Galina V. Shurin, et al.. (2022). Sensory Nerves Impede the Formation of Tertiary Lymphoid Structures and Development of Protective Antimelanoma Immune Responses. Cancer Immunology Research. 10(9). 1141–1154. 27 indexed citations
8.
Skums, Pavel, et al.. (2022). SOPHIE: Viral outbreak investigation and transmission history reconstruction in a joint phylogenetic and network theory framework. Cell Systems. 13(10). 844–856.e4. 5 indexed citations
9.
Knyazev, Sergey, Anupama Shankar, Alexander Artyomenko, et al.. (2021). Accurate assembly of minority viral haplotypes from next-generation sequencing through efficient noise reduction. Nucleic Acids Research. 49(17). e102–e102. 34 indexed citations
10.
Tariq, Amna, Juan M. Banda, Pavel Skums, et al.. (2021). Transmission dynamics and forecasts of the COVID-19 pandemic in Mexico, March-December 2020. PLoS ONE. 16(7). e0254826–e0254826. 17 indexed citations
11.
Knyazev, Sergey, et al.. (2021). Scalable Reconstruction of SARS-CoV-2 Phylogeny with Recurrent Mutations. Journal of Computational Biology. 28(11). 1130–1141.
12.
Валентович, Л. Н., et al.. (2021). SARS-CoV-2 transmission dynamics in Belarus in 2020 revealed by genomic and incidence data analysis. Communications Medicine. 1(1). 31–31. 5 indexed citations
13.
Lara, James, et al.. (2020). Quantitative differences between intra-host HCV populations from persons with recently established and persistent infections. Virus Evolution. 7(1). veaa103–veaa103. 11 indexed citations
14.
Skums, Pavel, et al.. (2019). Inference of clonal selection in cancer populations using single-cell sequencing data. Bioinformatics. 35(14). i398–i407. 10 indexed citations
15.
Campo, David S., et al.. (2018). Fast estimation of genetic relatedness between members of heterogeneous populations of closely related genomic variants. BMC Bioinformatics. 19(S11). 360–360. 2 indexed citations
16.
17.
Dimitrova, Zoya, David S. Campo, Sumathi Ramachandran, et al.. (2012). Evaluation of viral heterogeneity using next-generation sequencing, end-point limiting-dilution and mass spectrometry. In Silico Biology. 11(5-6). 183–192. 14 indexed citations
18.
Skums, Pavel, David S. Campo, Zoya Dimitrova, et al.. (2012). Numerical detection, measuring and analysis of differential interferon resistance for individual HCV intra-host variants and its influence on the therapy response. In Silico Biology. 11(5-6). 263–269. 8 indexed citations
19.
Dimitrova, Zoya, David S. Campo, Sumathi Ramachandran, et al.. (2011). Assessments of intra- and inter-host diversity of hepatitis C virus using Next Generation Sequencing and Mass spectrometry. 7. 79–86. 1 indexed citations
20.
Skums, Pavel, et al.. (2008). Edge intersection graphs of linear 3-uniform hypergraphs. Discrete Mathematics. 309(11). 3500–3517. 4 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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