Andreas Persidis
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Artificial Intelligence top 10%
- Endocrinology, Diabetes and Metabolism top 10%
- Immunology
- Co-authors
- Christos AndronisSpyros DeftereosAris PersidisAnuj SharmaIdit LaviNaomi GronichGad RennertNicholas M. P. King
- Topics
- Semantic Web and Ontologies (9 papers)Biomedical Text Mining and Ontologies (6 papers)Bioinformatics and Genomic Networks (6 papers)
- Cited by
- Computational Theory and MathematicsEndocrinology, Diabetes and MetabolismArtificial Intelligence
- Partner nations
- United KingdomUnited StatesItaly
In The Last Decade
Andreas Persidis
24 papers receiving 592 citations
Peers
Comparison fields: 5 of 125
- Molecular Biology 317
- Computational Theory and Mathematics 161
- Artificial Intelligence 149
- Endocrinology, Diabetes and Metabolism 102
- Immunology 50
Countries citing papers authored by Andreas Persidis
This map shows the geographic impact of Andreas Persidis'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 Andreas Persidis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Persidis more than expected).
Fields of papers citing papers by Andreas Persidis
This network shows the impact of papers produced by Andreas Persidis. 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 Andreas Persidis. The network helps show where Andreas Persidis may publish in the future.
Co-authorship network of co-authors of Andreas Persidis
This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Persidis. A scholar is included among the top collaborators of Andreas Persidis 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 Andreas Persidis. Andreas Persidis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 1 | |
| 3 | 88 | |
| 4 | 163 | |
| 5 | 23 | |
| 6 | 56 | |
| 7 | 11 | |
| 8 | 1 | |
| 9 | 42 | |
| 10 | 26 | |
| 11 | 3 | |
| 12 | 10 | |
| 13 | 17 | |
| 14 | 1 | |
| 15 | Integrated document and knowledge management for the knowledge-based enterprise | 3 |
| 16 | 24 | |
| 17 | 1 | |
| 18 | 6 | |
| 19 | 2 | |
| 20 | 5 |
About Andreas Persidis
Andreas Persidis is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Health Information Management, having authored 25 papers that have together received 651 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (9 papers), Biomedical Text Mining and Ontologies (6 papers) and Bioinformatics and Genomic Networks (6 papers). The work is most often cited by research in Computational Theory and Mathematics (161 citations), Endocrinology, Diabetes and Metabolism (102 citations) and Artificial Intelligence (149 citations). Andreas Persidis has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include Christos Andronis, Spyros Deftereos, Aris Persidis, Anuj Sharma, Idit Lavi, Naomi Gronich, Gad Rennert, Nicholas M. P. King, Fabio Rinaldi and Kaarel Kaljurand. Their work appears in journals such as Nature Biotechnology, Diabetes Care and Drug Discovery Today.
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.