Karin Kolmodin

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

Impact in

Papers in

Karin Kolmodin

20 papers receiving 1.1k citations

Peers

Karin Kolmodin
Comparison fields: 5 of 98
  • Computational Theory and Mathematics 303
  • Pharmacology 88
  • Molecular Biology 684
  • Organic Chemistry 235
  • Pharmacology 135
Replace Nam Sook Kang with:
Nam Sook Kang South Korea
Iain M. McLay United Kingdom
Owen Callaghan United States
Wolfgang Guba Switzerland
John W. Clader United States
Osman Güner United States
Brian Springthorpe United Kingdom
Rita Maria Concetta Di Martino Italy
Jon A. Erickson United States
Yong Seo Cho South Korea
Karin Kolmodin relative to Nam Sook Kang South Korea Nam Sook Kang's profile →
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 201825
2 20149
3 201334
4 201234
5 2012107
6 201256
7 201021
8 200958
9 200788
10 200416
11 200214
12 200185
13 200174
14 199923
15 1999131
16 199914
17 19999
18 199922
19 19991
20 1998289

About Karin Kolmodin

Karin Kolmodin is a scholar working on Computational Theory and Mathematics, Pharmacology, Physiology, Molecular Biology 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), ATP Synthase and ATPases Research (6 papers), Protein Tyrosine Phosphatases (6 papers), Alzheimer's disease research and treatments (5 papers), Cholinesterase and Neurodegenerative Diseases (4 papers), Tuberculosis Research and Epidemiology (2 papers), DNA and Nucleic Acid Chemistry (2 papers) and Protein Structure and Dynamics (2 papers). The work is most often cited by research in Computational Theory and Mathematics (303 citations), Pharmacology (88 citations), Molecular Biology (684 citations), Organic Chemistry (235 citations) and Pharmacology (135 citations). Karin Kolmodin has collaborated with scholars based in Sweden, United States and United Kingdom. Frequent co-authors include Johan Åqvist, John Marelius, Isabella Feierberg, Johan Åqvist, Jan Florián, Arieh Warshel, Anders Hallberg, Sherry F. Queener, Johanna Fälting and Britt‐Marie Swahn. Their work appears in journals such as FEBS Letters, Journal of Medicinal Chemistry, Proteins Structure Function and Bioinformatics, Journal of the American Chemical Society and ACS Medicinal Chemistry Letters.

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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