Jean‐Lambert Pasteels

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

Jean‐Lambert Pasteels

55 papers receiving 1.0k citations

Peers

Jean‐Lambert Pasteels
Comparison fields: 5 of 111
  • Cancer Research 165
  • Genetics 112
  • Nutrition and Dietetics 144
  • Oncology 244
  • Biophysics 44
Replace Takeshi Kasajima with:
Takeshi Kasajima Japan
Philip M. Iannaccone United States
Tommi Heikura Finland
P.A. Bryon France
Giuseppe Giuffrè Italy
Christine G. Lian United States
Linda Beckers Netherlands
R Keijzer Netherlands
Yoshie Miura Japan
W. Robb MacLellan United States
Jean‐Lambert Pasteels relative to Takeshi Kasajima Japan Takeshi Kasajima's profile →
Citations per field
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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-authorship network

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
#Work
1 200312
2 199910
3 19981
4 199810
5 19975
6 199710
7 19961
8 199617
9 199511
10 199519
11 19959
12 199413
13 199439
14 199425
15 199336
16 199324
17 199215
18 19908
19 199022
20 198822

About Jean‐Lambert Pasteels

Jean‐Lambert Pasteels is a scholar working on Biophysics, Genetics, Oncology, Cancer Research and Pulmonary and Respiratory Medicine, having authored 55 papers that have together received 1.1k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (7 papers), 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 (6 papers), Prostate Cancer Treatment and Research (5 papers), Renal cell carcinoma treatment (4 papers) and Neuroblastoma Research and Treatments (4 papers). The work is most often cited by research in Cancer Research (165 citations), Genetics (112 citations), Nutrition and Dietetics (144 citations), Oncology (244 citations) and Biophysics (44 citations). Jean‐Lambert Pasteels has collaborated with scholars based in Belgium, France and United States. Frequent co-authors include Róbert Kiss, Isabelle Salmon, Rodrigo Moreno‐Reyes, Dominique Egrise, André Schoutens, Jean Nève, Jacques Brotchi, Myriam Remmelink, Roland van Velthoven and Michel Pétein. Their work appears in journals such as The Prostate, American Journal of Clinical Pathology, Cancer, Cytometry and Human Pathology.

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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