Jaap Twisk

3.6k citations
49 papers · 2.9k · h-index 27

Impact in

Papers in

    • Virus-based gene therapy research 12
    • Diabetes and associated disorders 11
    • Cholesterol and Lipid Metabolism 15

Jaap Twisk

49 papers receiving 2.9k citations

Peers

Jaap Twisk
Comparison fields: 5 of 94
  • Genetics 824
  • Endocrinology, Diabetes and Metabolism 416
  • Oncology 651
  • Surgery 1.0k
  • Cardiology and Cardiovascular Medicine 487
Replace Martine I. Darville with:
Martine I. Darville Belgium
Alessandro Cama Italy
Phoebe E. Fielding United States
S K Karathanasis United States
Damien C. Wilpitz United States
Runpei Wu United States
Yasuhiro Mitsuuchi United States
Sally P.A. McCormick New Zealand
Jeff L. Ellsworth United States
Lawrence S. Argetsinger United States
Jaap Twisk relative to Martine I. Darville Belgium Martine I. Darville's profile →
Citations per field
00.5×
Martine I. Darville · 1×
Citations per year

Countries citing papers authored by Jaap Twisk

Since Specialization
Citations

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

Fields of papers citing papers by Jaap Twisk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012308
2 2002303
3 2000202
4 2003198
5 2008146
6 2012123
7 2016113
8 2004110
9 2008110
10 2013107
11 199597
12 200397
13 200988
14 199787
15 200669
16 199563
17 200463
18 199362
19 200660
20 200555

About Jaap Twisk

Jaap Twisk is a scholar working on Genetics, Surgery, Oncology, Molecular Biology and Cardiology and Cardiovascular Medicine, having authored 49 papers that have together received 2.9k indexed citations. Recurring topics across this work include Cholesterol and Lipid Metabolism (15 papers), Drug Transport and Resistance Mechanisms (12 papers), Virus-based gene therapy research (12 papers), Diabetes and associated disorders (11 papers), Lipid metabolism and disorders (8 papers), Liver Disease Diagnosis and Treatment (4 papers), Cancer, Lipids, and Metabolism (4 papers) and Peroxisome Proliferator-Activated Receptors (4 papers). The work is most often cited by research in Genetics (824 citations), Endocrinology, Diabetes and Metabolism (416 citations), Oncology (651 citations), Surgery (1.0k citations) and Cardiology and Cardiovascular Medicine (487 citations). Jaap Twisk has collaborated with scholars based in Netherlands, Canada and United States. Frequent co-authors include Theo J.C. van Berkel, Miranda Van Eck, Diane Brisson, Daniel Gaudet, I. Sophie T. Bos, Julie Méthot, Jan Albert Kuivenhoven, J. de Wal, John J.P. Kastelein and Menno Hoekstra. Their work appears in journals such as Human Gene Therapy, Biochemical Journal, Arteriosclerosis Thrombosis and Vascular Biology, Gene and Journal of Lipid 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.

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