Karin Melén

1.3k citations
9 papers · 1.0k · h-index 9

Impact in

  • Genetics top 10%
    • Bacterial Genetics and Biotechnology
    • RNA and protein synthesis mechanisms
    • Machine Learning in Bioinformatics
    • Protein Structure and Dynamics
    • Lipid Membrane Structure and Behavior

Papers in

    • Machine Learning in Bioinformatics 6
    • RNA and protein synthesis mechanisms 6
    • Glycosylation and Glycoproteins Research 3
    • Genomics and Phylogenetic Studies 2
    • Bacterial Genetics and Biotechnology 3

Karin Melén

9 papers receiving 1.0k citations

Peers

Karin Melén
Comparison fields: 5 of 89
  • Genetics 304
  • Molecular Biology 755
  • Endocrinology 49
  • Molecular Medicine 45
  • Biochemistry 46
Replace Mika Yoshimura with:
Mika Yoshimura Japan
Joan E. McEwen United States
Larisa E. Cybulski Argentina
Hiromi Daiyasu Japan
Toru Nakayashiki Japan
Horia Todor United States
Eva Schäfer Germany
Celeste Peterson United States
Junsang Ko South Korea
Angelo Palmigiano Italy
Karin Melén relative to Mika Yoshimura Japan Mika Yoshimura's profile →
Citations per field
00.5×1.5×
Mika Yoshimura · 1×
Citations per year

Countries citing papers authored by Karin Melén

Since Specialization
Citations

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

Fields of papers citing papers by Karin Melén

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Karin Melén, 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 Melén Line = papers co-authored together Karin Melén links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 2005390
2 2003168
3 2005150
4 2006109
5 200481
6 200354
7 200545
8 200629
9 199613

About Karin Melén

Karin Melén is a scholar working on Molecular Biology, Genetics, Biomaterials, Cell Biology and Physiology, having authored 9 papers that have together received 1.0k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (6 papers), RNA and protein synthesis mechanisms (6 papers), Glycosylation and Glycoproteins Research (3 papers), Bacterial Genetics and Biotechnology (3 papers), Genomics and Phylogenetic Studies (2 papers), Alzheimer's disease research and treatments (1 paper), Supramolecular Self-Assembly in Materials (1 paper) and Cerebral Palsy and Movement Disorders (1 paper). The work is most often cited by research in Genetics (304 citations), Molecular Biology (755 citations), Endocrinology (49 citations), Molecular Medicine (45 citations) and Biochemistry (46 citations). Karin Melén has collaborated with scholars based in Sweden, United States and Denmark. Frequent co-authors include Gunnar von Heijne, Mikaela Rapp, Daniel O. Daley, David Drew, Erik Granseth, Anders Krogh, Hyun Kim, Marie Österberg, Hanna Laudon and Bengt Winblad. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry, Journal of Molecular Biology, Protein Science and Developmental Medicine & Child Neurology.

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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