Karolina Pavic

12 papers and 260 indexed citations i.

About

Karolina Pavic is a scholar working on Molecular Biology, Computational Theory and Mathematics and Genetics. According to data from OpenAlex, Karolina Pavic has authored 12 papers receiving a total of 260 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 3 papers in Computational Theory and Mathematics and 2 papers in Genetics. Recurrent topics in Karolina Pavic’s work include Protein Tyrosine Phosphatases (5 papers), Protein Kinase Regulation and GTPase Signaling (4 papers) and Computational Drug Discovery Methods (3 papers). Karolina Pavic is often cited by papers focused on Protein Tyrosine Phosphatases (5 papers), Protein Kinase Regulation and GTPase Signaling (4 papers) and Computational Drug Discovery Methods (3 papers). Karolina Pavic collaborates with scholars based in Finland, Germany and Luxembourg. Karolina Pavic's co-authors include Maja Köhn, Pablo Ríos, Guangyou Duan, Jukka Westermarck, Otto Kauko, Jiao Wang, Juha Okkeri, Grzegorz Sarek, Wenqing Xu and Zhizhi Wang and has published in prestigious journals such as Journal of Biological Chemistry, Biochemistry and Clinical Cancer Research.

In The Last Decade

Co-authorship network of co-authors of Karolina Pavic i

Fields of papers citing papers by Karolina Pavic

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Karolina Pavic

Since Specialization
Citations

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

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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2025