Jürgen Jänes

1.6k citations
9 papers · 331 indexed · 1 hit paper · h-index 7
  • Aging top 5%
    • Genetics, Aging, and Longevity in Model Organisms 2
    • Machine Learning in Bioinformatics 3
    • Genomics and Phylogenetic Studies 3
    • Bioinformatics and Genomic Networks 2
    • RNA and protein synthesis mechanisms 2
    • Genomics and Chromatin Dynamics 2
    • Metabolomics and Mass Spectrometry Studies 1
    • Genomics and Rare Diseases 1

Jürgen Jänes

9 papers receiving 328 citations

Hit Papers

Clustering predicted structures at the scale of the known...160202320262024202550100150

Peers

Jürgen Jänes
Comparison fields: 5 of 67
  • Aging 52
  • Molecular Biology 269
  • Health Informatics 3
  • Structural Biology 2
  • Genetics 38
Replace Arjun N. Sasikumar with:
Arjun N. Sasikumar United States
Sophie Zaaijer United States
Laura Le Breton Germany
Diane C. DeZwaan United States
Nimit Jain United States
Carmina Angelica Perez Romero France
Wanyuan Ao United States
Jonathan J. Turner United States
Ryan R. Murray United States
Benjamin L. Woods United States
Jürgen Jänes relative to Arjun N. Sasikumar United States Arjun N. Sasikumar's profile →
Citations per field
00.5×
Arjun N. Sasikumar · 1×
Citations per year

Countries citing papers authored by Jürgen Jänes

Since Specialization
Citations

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

Fields of papers citing papers by Jürgen Jänes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Jürgen Jänes, 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 Jürgen Jänes Line = papers co-authored together Jürgen Jänes links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 20252
2 202418
3 202410
4 20243
5
Clustering predicted structures at the scale of the known protein universebreakdown →
2023160
6 202031
7 201862
8 201521
9 200724

About Jürgen Jänes

Jürgen Jänes is a scholar working on Aging, Molecular Biology and Pharmacology, having authored 9 papers that have together received 331 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (3 papers), Genomics and Phylogenetic Studies (3 papers), Genetics, Aging, and Longevity in Model Organisms (2 papers), Bioinformatics and Genomic Networks (2 papers), RNA and protein synthesis mechanisms (2 papers), Genomics and Chromatin Dynamics (2 papers), Genomics and Rare Diseases (1 paper) and Metabolomics and Mass Spectrometry Studies (1 paper). The work is most often cited by research in Aging (52 citations), Molecular Biology (269 citations) and Health Informatics (3 citations). Jürgen Jänes has collaborated with scholars based in United Kingdom, Switzerland and Austria. Frequent co-authors include Pedro Beltrão, Mihály Váradi, Tanita Wein, Inigo Barrio‐Hernandez, Milot Mirdita, Sameer Velankar, Cameron L. M. Gilchrist, Martin Steinegger, Dong Yan and Jacques Serizay. Their work appears in journals such as Nature, Nucleic Acids Research and Nature Biotechnology.

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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