Jane Widmer
Impact in
- Physiology top 5%
- Adipose Tissue and Metabolism
- Calcium signaling and nucleotide metabolism
- Molecular Biology top 10%
- Metabolism, Diabetes, and Cancer
- Fungal and yeast genetics research
Papers in
-
- Metabolism, Diabetes, and Cancer 4
- Peroxisome Proliferator-Activated Receptors 4
- Fungal and yeast genetics research 2
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- Metabolism and Genetic Disorders 3
- Co-authors
- Lee A. Witters (9 shared papers)David Stapleton (5 shared papers)Bruce E. Kemp (5 shared papers)Guang Gao (5 shared papers)Carolina Fernández (3 shared papers)Trazel Teh (3 shared papers)Ken I. Mitchelhill (2 shared papers)Belinda J. Michell (2 shared papers)
- Journals
- Journal of Biological Chemistry (4 papers)Biochemical Journal (2 papers)Biochimica et Biophysica Acta (BBA) - Molecular Cell Research (1 paper)Biochemical and Biophysical Research Communications (1 paper)Cytogenetic and Genome Research (1 paper)
- Partner nations
- United StatesAustraliaDenmark
In The Last Decade
Jane Widmer
9 papers receiving 1.1k citations
Jane Widmer's Hit Papers
Peers
Comparison fields: 5 of 75
- Physiology 98
- Molecular Biology 954
- Surgery 456
- Endocrinology, Diabetes and Metabolism 150
- Physiology 229
Countries citing papers authored by Jane Widmer
This map shows the geographic impact of Jane Widmer'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 Jane Widmer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jane Widmer more than expected).
Fields of papers citing papers by Jane Widmer
This network shows the impact of papers produced by Jane Widmer. 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 Jane Widmer. The network helps show where Jane Widmer may publish in the future.
Co-authors
The 21 scholars most cited alongside Jane Widmer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Mammalian AMP-activated Protein Kinase Subfamily Hit paper breakdown → | 1996 | 556 |
| 2 | 1996 | 161 | |
| 3 | 1996 | 113 | |
| 4 | 1994 | 111 | |
| 5 | 1995 | 71 | |
| 6 | 1996 | 62 | |
| 7 | 1997 | 40 | |
| 8 | 1993 | 17 | |
| 9 | 1993 | 2 |
About Jane Widmer
Jane Widmer is a scholar working on Molecular Biology, Clinical Biochemistry, Cell Biology, Cancer Research and Materials Chemistry, having authored 9 papers that have together received 1.1k indexed citations. Recurring topics across this work include Metabolism, Diabetes, and Cancer (4 papers), Peroxisome Proliferator-Activated Receptors (4 papers), Metabolism and Genetic Disorders (3 papers), Biotin and Related Studies (3 papers), Cancer, Hypoxia, and Metabolism (2 papers), Enzyme Structure and Function (2 papers), Fungal and yeast genetics research (2 papers) and Pancreatic function and diabetes (1 paper). The work is most often cited by research in Physiology (98 citations), Molecular Biology (954 citations), Surgery (456 citations), Endocrinology, Diabetes and Metabolism (150 citations) and Physiology (229 citations). Jane Widmer has collaborated with scholars based in United States, Australia and Denmark. Frequent co-authors include Lee A. Witters, David Stapleton, Bruce E. Kemp, Guang Gao, Carolina Fernández, Trazel Teh, Ken I. Mitchelhill, Belinda J. Michell, Colin M. House and Timothy M. Cox. Their work appears in journals such as Journal of Biological Chemistry, Biochemical Journal, Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, Biochemical and Biophysical Research Communications and Cytogenetic and Genome Research.
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.