Karin Kolmodin

1.7k citations
20 papers · 1.1k · h-index 15

Impact in

Papers in

Karin Kolmodin

20 papers receiving 1.1k citations

Peers

Karin Kolmodin
Comparison fields: 5 of 97
  • Computational Theory and Mathematics 287
  • Molecular Biology 666
  • Pharmacology 78
  • Pharmacology 130
  • Organic Chemistry 235
Replace Nam Sook Kang with:
Nam Sook Kang South Korea
Owen Callaghan United States
Michael Czarniecki United States
Iain M. McLay United Kingdom
John W. Clader United States
Konrad F. Koehler United States
Wolfgang Guba Switzerland
Yong Seo Cho South Korea
Rita Maria Concetta Di Martino Italy
Osman Güner United States
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Citations per field
00.5×1.7×
Nam Sook Kang · 1×
Citations per year

Countries citing papers authored by Karin Kolmodin

Since Specialization
Citations

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

Fields of papers citing papers by Karin Kolmodin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Karin Kolmodin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Karin Kolmodin Line = papers co-authored together Karin Kolmodin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 1998292
2 1999131
3 2012107
4 200789
5 200186
6 200174
7 200959
8 201256
9 201234
10 201334
11 201825
12 199923
13 199922
14 201021
15 200416
16 200214
17 199914
18 19999
19 20149
20 19991

About Karin Kolmodin

Karin Kolmodin is a scholar working on Molecular Biology, Computational Theory and Mathematics, Physiology, Pharmacology and Immunology, having authored 20 papers that have together received 1.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Protein Tyrosine Phosphatases (6 papers), ATP Synthase and ATPases Research (6 papers), Alzheimer's disease research and treatments (5 papers), Cholinesterase and Neurodegenerative Diseases (4 papers), Pneumocystis jirovecii pneumonia detection and treatment (2 papers), Tuberculosis Research and Epidemiology (2 papers) and Enzyme Structure and Function (2 papers). The work is most often cited by research in Computational Theory and Mathematics (287 citations), Molecular Biology (666 citations), Pharmacology (78 citations), Pharmacology (130 citations) and Organic Chemistry (235 citations). Karin Kolmodin has collaborated with scholars based in Sweden, United States and United Kingdom. Frequent co-authors include Johan Åqvist, Isabella Feierberg, John Marelius, Jan Florián, Johan Åqvist, Arieh Warshel, Sherry F. Queener, Anders Hallberg, Johanna Fälting and Britt‐Marie Swahn. Their work appears in journals such as Journal of Medicinal Chemistry, FEBS Letters, Proteins Structure Function and Bioinformatics, Biochemical and Biophysical Research Communications and Drug Metabolism Reviews.

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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