Pauline Kra

1.1k citations
7 papers · 811 indexed · h-index 5
Topics
Biomedical Text Mining and Ontologies (6 papers)Bioinformatics and Genomic Networks (4 papers)Computational Drug Discovery Methods (3 papers)
Partner nations
United StatesJapanSpain

In The Last Decade

Pauline Kra

7 papers receiving 754 citations

Peers

Pauline Kra
Comparison fields: 5 of 68
  • Molecular Biology 723
  • Artificial Intelligence 501
  • Computational Theory and Mathematics 60
  • Genetics 46
  • Information Systems 24
Replace Jasmin Šarić with:
Jasmin Šarić Germany
Michael Bada United States
Mariana Neves Germany
Steffen Schulze-Kremer Germany
Susanne M. Humphrey United States
Sylvain Gaudan United Kingdom
Lawrence W. Wright United States
Nicholas Sioutos United States
J Tsujii Japan
Robert Stevens United Kingdom
Pauline Kra relative to Jasmin Šarić Germany Jasmin Šarić's profile →
Citations per field
00.5×1.6×
Jasmin Šarić · 1×
Citations per year

Countries citing papers authored by Pauline Kra

Since Specialization
Citations

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

Fields of papers citing papers by Pauline Kra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pauline Kra

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

All Works

7 of 7 papers shown
#WorkIndexed citations
1
Automating terminological networks to link heterogeneous biomedical databases.
3
2 198
3 42
4 153
5 358
6 53
7 4

About Pauline Kra

Pauline Kra is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Molecular Biology, having authored 7 papers that have together received 811 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (6 papers), Bioinformatics and Genomic Networks (4 papers) and Computational Drug Discovery Methods (3 papers). The work is most often cited by research in Artificial Intelligence (501 citations), Molecular Biology (723 citations) and Computational Theory and Mathematics (60 citations). Pauline Kra has collaborated with scholars based in United States, Japan and Spain. Frequent co-authors include Andrey Rzhetsky, Michael Krauthammer, Carol Friedman, Hua Yu, Cynthia Friedman, Ivan Iossifov, Vasileios Hatzivassiloglou, Pablo Duboue, Mitzi Morris and W. John Wilbur. Their work appears in journals such as Bioinformatics, Journal of Biomedical Informatics and Eighteenth-Century Studies.

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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