Natalja Strelkowa

2.0k citations
12 papers · 1.1k indexed · 1 hit paper · h-index 6
Topics
Gene Regulatory Network Analysis (4 papers)Hepatitis C virus research (3 papers)HIV/AIDS drug development and treatment (3 papers)

In The Last Decade

Natalja Strelkowa

11 papers receiving 1.1k citations

Hit Papers

Approximate Bayesian computation scheme for parameter inf...20082026201420202008250500750

Peers

Natalja Strelkowa
Comparison fields: 5 of 133
  • Molecular Biology 358
  • Artificial Intelligence 249
  • Statistics and Probability 243
  • Genetics 196
  • Epidemiology 142
Replace Andreas Ipsen with:
Andreas Ipsen United Kingdom
Tina Toni United Kingdom
Peter Neal United Kingdom
Wei Tan United States
Pedro Puig Spain
Elina Numminen Finland
Jasmin Bachmann Germany
Elja Arjas Finland
Alberto Giovanni Busetto Switzerland
Marco A. R. Ferreira United States
Natalja Strelkowa relative to Andreas Ipsen United Kingdom Andreas Ipsen's profile →
Citations per field
00.5×1.7×
Andreas Ipsen · 1×
Citations per year

Countries citing papers authored by Natalja Strelkowa

Since Specialization
Citations

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

Fields of papers citing papers by Natalja Strelkowa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Natalja Strelkowa

This figure shows the co-authorship network connecting the top 25 collaborators of Natalja Strelkowa. A scholar is included among the top collaborators of Natalja Strelkowa 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 Natalja Strelkowa. Natalja Strelkowa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
#WorkIndexed citations
1 0
2 11
3 19
4 1
5 5
6
Toggling a Genetic Switch Using Reinforcement Learning
1
7 8
8 3
9 114
10 1
11 31
12
Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systemsbreakdown →
900

About Natalja Strelkowa

Natalja Strelkowa is a scholar working on Hepatology, Infectious Diseases and Genetics, having authored 12 papers that have together received 1.1k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (4 papers), Hepatitis C virus research (3 papers) and HIV/AIDS drug development and treatment (3 papers). The work is most often cited by research in Statistics and Probability (243 citations), Modeling and Simulation (134 citations) and Statistics, Probability and Uncertainty (84 citations). Natalja Strelkowa has collaborated with scholars based in Germany, Belgium and United Kingdom. Frequent co-authors include David Welch, Andreas Ipsen, Tina Toni, Michael P. H. Stumpf, Michael Lässig, Mauricio Barahona, Guy‐Bart Stan, James Anderson, Thomas Douglas and Julian Savulescu. Their work appears in journals such as Journal of Clinical Oncology, Genetics and Journal of Hepatology.

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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