Jean‐Lambert Pasteels

1.2k citations
55 papers · 1.1k · h-index 20

Impact in

Papers in

Jean‐Lambert Pasteels

55 papers receiving 1.0k citations

Peers

Jean‐Lambert Pasteels
Comparison fields: 5 of 111
  • Genetics 105
  • Cancer Research 139
  • Nutrition and Dietetics 138
  • Oncology 186
  • Biophysics 39
Replace Takeshi Kasajima with:
Takeshi Kasajima Japan
Giuseppe Giuffrè Italy
Linda Beckers Netherlands
Hans‐Reiner Figulla Germany
Stefan Zöllner Germany
Tommi Heikura Finland
Mary Richardson Canada
Yoshie Miura Japan
J. C. F. Poole United Kingdom
Holger Winkels Germany
Jean‐Lambert Pasteels relative to Takeshi Kasajima Japan Takeshi Kasajima's profile →
Citations per field
00.5×4.9×
Takeshi Kasajima · 1×
Citations per year

Countries citing papers authored by Jean‐Lambert Pasteels

Since Specialization
Citations

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

Fields of papers citing papers by Jean‐Lambert Pasteels

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean‐Lambert Pasteels. 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 Jean‐Lambert Pasteels. The network helps show where Jean‐Lambert Pasteels may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001189
2 199162
3 199851
4 199243
5 199439
6 199338
7 198936
8 199330
9 199030
10 199327
11 199827
12 199426
13 199326
14 199226
15
Estradiol-dependent collagenolytic enzyme activity in long-term organ culture of human breast cancer.
197526
16 198825
17 199325
18 199325
19 199023
20 199720

About Jean‐Lambert Pasteels

Jean‐Lambert Pasteels is a scholar working on Pulmonary and Respiratory Medicine, Oncology, Surgery, Molecular Biology and Radiology, Nuclear Medicine and Imaging, having authored 55 papers that have together received 1.1k indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (7 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Glioma Diagnosis and Treatment (6 papers), Cancer Cells and Metastasis (5 papers), Cancer Genomics and Diagnostics (5 papers), Renal cell carcinoma treatment (4 papers), Prostate Cancer Treatment and Research (4 papers) and Gout, Hyperuricemia, Uric Acid (3 papers). The work is most often cited by research in Genetics (105 citations), Cancer Research (139 citations), Nutrition and Dietetics (138 citations), Oncology (186 citations) and Biophysics (39 citations). Jean‐Lambert Pasteels has collaborated with scholars based in Belgium, France and United States. Frequent co-authors include Róbert Kiss, Isabelle Salmon, André Schoutens, Rodrigo Moreno‐Reyes, Jean Nève, Dominique Egrise, Myriam Remmelink, Jacques Brotchi, Michel Pétein and Roland van Velthoven. Their work appears in journals such as American Journal of Clinical Pathology, The Prostate, The Journal of Pathology, Cytometry and Cancer.

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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