D Imbs
Impact in
-
- Hepatocellular Carcinoma Treatment and Prognosis
- Modeling and Simulation top 10%
- Mathematical Biology Tumor Growth
Papers in
- Epidemiology 10
- Virology and Viral Diseases 10
- Oncology 7
- Cancer Treatment and Pharmacology 3
- Colorectal Cancer Treatments and Studies 3
- Co-authors
- Joseph Ciccolini (6 shared papers)Étienne Chatelut (5 shared papers)Bruno Lacarelle (4 shared papers)Fabienne Thomas (2 shared papers)Mélanie White‐Koning (2 shared papers)Dominique Barbolosi (4 shared papers)Thierry Lafont (3 shared papers)Sébastien Benzekry (2 shared papers)
- Journals
- Cancer Chemotherapy and Pharmacology (3 papers)Blood (2 papers)HemaSphere (2 papers)Oncotarget (2 papers)CPT Pharmacometrics & Systems Pharmacology (1 paper)
- Partner nations
- FranceUnited KingdomSwitzerland
In The Last Decade
D Imbs
28 papers receiving 302 citations
Peers
Comparison fields: 5 of 61
- Hepatology 32
- Modeling and Simulation 19
- Hematology 42
- Oncology 94
- Genetics 28
Countries citing papers authored by D Imbs
This map shows the geographic impact of D Imbs'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 D Imbs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D Imbs more than expected).
Fields of papers citing papers by D Imbs
This network shows the impact of papers produced by D Imbs. 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 D Imbs. The network helps show where D Imbs may publish in the future.
Co-authors
The 25 scholars most cited alongside D Imbs, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 46 | |
| 2 | 2015 | 34 | |
| 3 | 2016 | 32 | |
| 4 | 2018 | 26 | |
| 5 | 2017 | 26 | |
| 6 | 2015 | 25 | |
| 7 | 2017 | 19 | |
| 8 | 2014 | 17 | |
| 9 | 2017 | 13 | |
| 10 | 2016 | 12 | |
| 11 | Cell-mediated immune reactions in measles. | 1980 | 12 |
| 12 | 1979 | 7 | |
| 13 | 2021 | 6 | |
| 14 | 2022 | 6 | |
| 15 | 2022 | 4 | |
| 16 | Study of interaction between IgG and IgM antibodies against rubella virus by the immunofluorescence method. | 1979 | 4 |
| 17 | 2021 | 3 | |
| 18 | Cell- and antibody-mediated responses to measles and mumps viruses in experimental animals. | 1978 | 2 |
| 19 | 2021 | 2 | |
| 20 | [Occurrence of antibodies against epidemic parotitis virus among the population of Poland]. | 1984 | 2 |
About D Imbs
D Imbs is a scholar working on Epidemiology, Oncology, Hematology, Molecular Biology and Genetics, having authored 29 papers that have together received 310 indexed citations. Recurring topics across this work include Virology and Viral Diseases (10 papers), Blood groups and transfusion (4 papers), Hemoglobinopathies and Related Disorders (4 papers), Cancer Treatment and Pharmacology (3 papers), Colorectal Cancer Treatments and Studies (3 papers), Syphilis Diagnosis and Treatment (2 papers), Angiogenesis and VEGF in Cancer (2 papers) and Chemotherapy-induced organ toxicity mitigation (2 papers). The work is most often cited by research in Hepatology (32 citations), Modeling and Simulation (19 citations), Hematology (42 citations), Oncology (94 citations) and Genetics (28 citations). D Imbs has collaborated with scholars based in France, United Kingdom and Switzerland. Frequent co-authors include Joseph Ciccolini, Étienne Chatelut, Bruno Lacarelle, Fabienne Thomas, Mélanie White‐Koning, Dominique Barbolosi, Thierry Lafont, Sébastien Benzekry, Sylvie Négrier and Chloé Sauzay. Their work appears in journals such as Cancer Chemotherapy and Pharmacology, Blood, HemaSphere, Oncotarget and CPT Pharmacometrics & Systems Pharmacology.
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.