Anke Toenjes

1.2k citations
4 papers · 47 · h-index 3

Impact in

Papers in

    • Machine Learning in Bioinformatics 1
    • Bioinformatics and Genomic Networks 1
    • Metabolomics and Mass Spectrometry Studies 1
    • Liver Disease Diagnosis and Treatment 2

Anke Toenjes

4 papers receiving 46 citations

Peers

Anke Toenjes
Comparison fields: 5 of 33
  • Radiological and Ultrasound Technology 5
  • Endocrinology, Diabetes and Metabolism 10
  • Clinical Biochemistry 3
  • Biological Psychiatry 1
  • Obstetrics and Gynecology 3
Replace Wei-Sin Yang with:
Wei-Sin Yang Taiwan
Lisa C. Yeh United States
Donna K. Arnett United States
Eva Serra United Kingdom
Isabel Perez-Corral Spain
Liang Qin China
Giulia Maggioni Italy
Carola Marzi Germany
E Shlyakhto Russia
Isabel Correia Portugal
Anke Toenjes relative to Wei-Sin Yang Taiwan Wei-Sin Yang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Anke Toenjes

Since Specialization
Citations

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

Fields of papers citing papers by Anke Toenjes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

4 of 4 papers shown
#Work
1 201929
2 200610
3 20177
4 20191

About Anke Toenjes

Anke Toenjes is a scholar working on Molecular Biology, Epidemiology, Physiology, Surgery and Radiological and Ultrasound Technology, having authored 4 papers that have together received 47 indexed citations. Recurring topics across this work include Diet and metabolism studies (2 papers), Liver Disease Diagnosis and Treatment (2 papers), Machine Learning in Bioinformatics (1 paper), Bioinformatics and Genomic Networks (1 paper), Palliative Care and End-of-Life Issues (1 paper), Cardiac Arrest and Resuscitation (1 paper), Metabolomics and Mass Spectrometry Studies (1 paper) and Family and Patient Care in Intensive Care Units (1 paper). The work is most often cited by research in Radiological and Ultrasound Technology (5 citations), Endocrinology, Diabetes and Metabolism (10 citations), Clinical Biochemistry (3 citations), Biological Psychiatry (1 citation) and Obstetrics and Gynecology (3 citations). Anke Toenjes has collaborated with scholars based in Germany and United Kingdom. Frequent co-authors include Markus Loeffler, Uta Ceglarek, Holger Kirsten, Joachim Thiery, Michael Stümvoll, J Dittrich, Susen Becker, Frank Beutner, Markus Scholz and Hölger Thiele. Their work appears in journals such as Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, Journal of Hepatology, BMC Anesthesiology and Molecular Metabolism.

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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