Theodore Sakellaropoulos
- Artificial Intelligence top 1%
- Radiology, Nuclear Medicine and Imaging top 1%
- Molecular Biology top 10%
- Oncology top 10%
- Cancer Research top 5%
- Co-authors
- Aristotelis TsirigosDavid FenyöMatija SnuderlNarges RazavianNicolas CoudrayNavneet NarulaAndré L. MoreiraPaolo Ocampo
- Topics
- Computational Drug Discovery Methods (10 papers)Bioinformatics and Genomic Networks (8 papers)Genomics and Chromatin Dynamics (7 papers)
- Partner nations
- United StatesGreeceUnited Kingdom
In The Last Decade
Theodore Sakellaropoulos
30 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Artificial Intelligence 1.1k
- Radiology, Nuclear Medicine and Imaging 994
- Molecular Biology 862
- Oncology 410
- Cancer Research 393
Countries citing papers authored by Theodore Sakellaropoulos
This map shows the geographic impact of Theodore Sakellaropoulos'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 Theodore Sakellaropoulos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Theodore Sakellaropoulos more than expected).
Fields of papers citing papers by Theodore Sakellaropoulos
This network shows the impact of papers produced by Theodore Sakellaropoulos. 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 Theodore Sakellaropoulos. The network helps show where Theodore Sakellaropoulos may publish in the future.
Co-authorship network of co-authors of Theodore Sakellaropoulos
This figure shows the co-authorship network connecting the top 25 collaborators of Theodore Sakellaropoulos. A scholar is included among the top collaborators of Theodore Sakellaropoulos 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 Theodore Sakellaropoulos. Theodore Sakellaropoulos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 2 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 7 | |
| 6 | 27 | |
| 7 | 10 | |
| 8 | 214 | |
| 9 | 1 | |
| 10 | 24 | |
| 11 | 13 | |
| 12 | 9 | |
| 13 | Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learningbreakdown → | 1738 |
| 14 | 47 | |
| 15 | 22 | |
| 16 | 67 | |
| 17 | Identification of drug-specific pathways based on gene expression data: application to drug induced lung injury | 1 |
| 18 | 2 | |
| 19 | 3 | |
| 20 | 38 |
About Theodore Sakellaropoulos
Theodore Sakellaropoulos is a scholar working on Computational Theory and Mathematics, Biophysics and Molecular Biology, having authored 30 papers that have together received 2.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (10 papers), Bioinformatics and Genomic Networks (8 papers) and Genomics and Chromatin Dynamics (7 papers). The work is most often cited by research in Health Informatics (150 citations), Radiology, Nuclear Medicine and Imaging (994 citations) and Biophysics (228 citations). Theodore Sakellaropoulos has collaborated with scholars based in United States, Greece and United Kingdom. Frequent co-authors include Aristotelis Tsirigos, David Fenyö, Matija Snuderl, Narges Razavian, Nicolas Coudray, Navneet Narula, André L. Moreira, Paolo Ocampo, Leonidas G. Alexopoulos and Iannis Aifantis. Their work appears in journals such as Nature Medicine, Nature Communications and Nature Biotechnology.
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.