Remzi Çelebi
- Computational Theory and Mathematics top 5%
- Molecular Biology
- Artificial Intelligence
- Materials Chemistry
- Pharmacology
- Co-authors
- Michel DumontierOğuz DikenelliOliver Bear Don’t WalkAhmed HassanSandeep AyyarTobias KuhnLars RidderJoão Moreira
- Topics
- Biomedical Text Mining and Ontologies (7 papers)Computational Drug Discovery Methods (7 papers)Bioinformatics and Genomic Networks (4 papers)
- Partner nations
- NetherlandsTürkiyeUnited States
In The Last Decade
Remzi Çelebi
13 papers receiving 187 citations
Peers
Comparison fields: 5 of 58
- Computational Theory and Mathematics 117
- Molecular Biology 114
- Artificial Intelligence 40
- Materials Chemistry 21
- Pharmacology 15
Countries citing papers authored by Remzi Çelebi
This map shows the geographic impact of Remzi Çelebi'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 Remzi Çelebi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Remzi Çelebi more than expected).
Fields of papers citing papers by Remzi Çelebi
This network shows the impact of papers produced by Remzi Çelebi. 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 Remzi Çelebi. The network helps show where Remzi Çelebi may publish in the future.
Co-authorship network of co-authors of Remzi Çelebi
This figure shows the co-authorship network connecting the top 25 collaborators of Remzi Çelebi. A scholar is included among the top collaborators of Remzi Çelebi 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 Remzi Çelebi. Remzi Çelebi 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 | 3 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | Metadata standards for the FAIR sharing of vector embeddings in Biomedicine | 0 |
| 7 | 12 | |
| 8 | 69 | |
| 9 | 75 | |
| 10 | 12 | |
| 11 | Machine Learning based Drug Indication Prediction using Linked Open Data | 1 |
| 12 | 9 | |
| 13 | Link Prediction for Drug-Drug Interaction Network | 1 |
| 14 | 2 | |
| 15 | 0 |
About Remzi Çelebi
Remzi Çelebi is a scholar working on Health Informatics, Computational Theory and Mathematics and Health Information Management, having authored 15 papers that have together received 192 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (7 papers), Computational Drug Discovery Methods (7 papers) and Bioinformatics and Genomic Networks (4 papers). The work is most often cited by research in Computational Theory and Mathematics (117 citations), Toxicology (12 citations) and Health Informatics (4 citations). Remzi Çelebi has collaborated with scholars based in Netherlands, Türkiye and United States. Frequent co-authors include Michel Dumontier, Oğuz Dikenelli, Oliver Bear Don’t Walk, Ahmed Hassan, Sandeep Ayyar, Tobias Kuhn, Lars Ridder, João Moreira, Leo Sauermann and Linda Rieswijk. Their work appears in journals such as Scientific Reports, BMC Bioinformatics and Journal of Food Composition and Analysis.
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.