Pierre Lebrun
- Molecular Biology
- Materials Chemistry
- Analytical Chemistry top 5%
- Pharmaceutical Science top 5%
- Spectroscopy top 10%
- Co-authors
- Péter TompaKris PauwelsEric ZiémonsLauranne NetchacovitchSimone KosolFabrice KrierRoberta PierattelliIsabella C. Felli
- Topics
- Business Process Modeling and Analysis (4 papers)Big Data and Business Intelligence (3 papers)Protein Structure and Dynamics (3 papers)
In The Last Decade
Pierre Lebrun
28 papers receiving 657 citations
Peers
Comparison fields: 5 of 122
- Molecular Biology 322
- Materials Chemistry 151
- Analytical Chemistry 86
- Pharmaceutical Science 83
- Spectroscopy 73
Countries citing papers authored by Pierre Lebrun
This map shows the geographic impact of Pierre Lebrun'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 Pierre Lebrun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pierre Lebrun more than expected).
Fields of papers citing papers by Pierre Lebrun
This network shows the impact of papers produced by Pierre Lebrun. 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 Pierre Lebrun. The network helps show where Pierre Lebrun may publish in the future.
Co-authorship network of co-authors of Pierre Lebrun
This figure shows the co-authorship network connecting the top 25 collaborators of Pierre Lebrun. A scholar is included among the top collaborators of Pierre Lebrun based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pierre Lebrun. Pierre Lebrun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 15 | |
| 3 | 50 | |
| 4 | 3 | |
| 5 | 6 | |
| 6 | 28 | |
| 7 | 32 | |
| 8 | 30 | |
| 9 | 59 | |
| 10 | 38 | |
| 11 | Méthodes chromatographiques génériques de criblage pour lutter contre les médicaments de qualité inférieure | 1 |
| 12 | USE OF MICRO-DAMS IN POTATO FURROWS TO REDUCE EROSION AND RUNOFF AND MINIMISE SURFACE WATER CONTAMINATION THROUGH PESTICIDES. | 12 |
| 13 | 48 | |
| 14 | 20 | |
| 15 | 164 | |
| 16 | 6 | |
| 17 | Extending OWL-S to Solve Enterprise Application IntegrationIssues | 1 |
| 18 | Managing the information system evolution: The microelectronics case study | 2 |
| 19 | High-strength and high-stiffness Al-Fe-Mn alloys fabricated by double mechanical alloying | 3 |
| 20 | Fabrication, structure, and properties of mechanically alloyed aluminum-alloys | 6 |
About Pierre Lebrun
Pierre Lebrun is a scholar working on Management Information Systems, Pharmaceutical Science and Statistics and Probability, having authored 30 papers that have together received 665 indexed citations. Recurring topics across this work include Business Process Modeling and Analysis (4 papers), Big Data and Business Intelligence (3 papers) and Protein Structure and Dynamics (3 papers). The work is most often cited by research in Pharmaceutical Science (83 citations), Biophysics (57 citations) and Analytical Chemistry (86 citations). Pierre Lebrun has collaborated with scholars based in Belgium, France and Hungary. Frequent co-authors include Péter Tompa, Kris Pauwels, Eric Ziémons, Lauranne Netchacovitch, Simone Kosol, Fabrice Krier, Roberta Pierattelli, Isabella C. Felli, Brigitte Évrard and Mihály Váradi. Their work appears in journals such as Nucleic Acids Research, PLoS ONE and Scientific Reports.
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.