Philippe Thomas
- Molecular Biology
- Artificial Intelligence top 5%
- Endocrine and Autonomic Systems top 5%
- Computational Theory and Mathematics top 10%
- Physiology
- Co-authors
- Ulf LeserDomonkos TikkJörg HakenbergTim RocktäschelMariana NevesIllés SoltHanspeter HerzelAngela Relógio
- Topics
- Biomedical Text Mining and Ontologies (17 papers)Topic Modeling (10 papers)Bioinformatics and Genomic Networks (6 papers)
- Partner nations
- GermanyUnited StatesHungary
In The Last Decade
Philippe Thomas
26 papers receiving 575 citations
Peers
Comparison fields: 5 of 88
- Molecular Biology 396
- Artificial Intelligence 252
- Endocrine and Autonomic Systems 125
- Computational Theory and Mathematics 59
- Physiology 59
Countries citing papers authored by Philippe Thomas
This map shows the geographic impact of Philippe Thomas'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 Philippe Thomas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philippe Thomas more than expected).
Fields of papers citing papers by Philippe Thomas
This network shows the impact of papers produced by Philippe Thomas. 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 Philippe Thomas. The network helps show where Philippe Thomas may publish in the future.
Co-authorship network of co-authors of Philippe Thomas
This figure shows the co-authorship network connecting the top 25 collaborators of Philippe Thomas. A scholar is included among the top collaborators of Philippe Thomas 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 Philippe Thomas. Philippe Thomas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 11 | |
| 3 | 8 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 6 | |
| 7 | 7 | |
| 8 | 3 | |
| 9 | 27 | |
| 10 | 120 | |
| 11 | WBI-DDI: Drug-Drug Interaction Extraction using Majority Voting | 51 |
| 12 | Experiences from Developing the Domain-Specific Entity Search Engine GeneView. | 0 |
| 13 | 30 | |
| 14 | Improving Distantly Supervised Extraction of Drug-Drug and Protein-Protein Interactions | 15 |
| 15 | 54 | |
| 16 | Not all links are equal: Exploiting Dependency Types for the Extraction of Protein-Protein Interactions from Text | 15 |
| 17 | Learning Protein Protein Interaction Extraction using Distant Supervision | 4 |
| 18 | Learning to Extract Protein-Protein Interactions using Distant Supervision | 2 |
| 19 | 31 | |
| 20 | 133 |
About Philippe Thomas
Philippe Thomas is a scholar working on Aging, Artificial Intelligence and Endocrine and Autonomic Systems, having authored 31 papers that have together received 602 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (17 papers), Topic Modeling (10 papers) and Bioinformatics and Genomic Networks (6 papers). The work is most often cited by research in Aging (43 citations), Endocrine and Autonomic Systems (125 citations) and Health Informatics (11 citations). Philippe Thomas has collaborated with scholars based in Germany, United States and Hungary. Frequent co-authors include Ulf Leser, Domonkos Tikk, Jörg Hakenberg, Tim Rocktäschel, Mariana Neves, Illés Solt, Hanspeter Herzel, Angela Relógio, Roman Klinger and Johannes Starlinger. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.
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.