Dénes Türei
- Molecular Biology top 5%
- Immunology top 10%
- Epidemiology top 10%
- Cancer Research top 10%
- Physiology top 10%
- Co-authors
- Julio Sáez-RodríguezTamás KorcsmárosLuz García‐AlonsoMahmoud M. IbrahimChristian H. HollandDezső MódosPéter CsermelyKatalin Lenti
- Topics
- Bioinformatics and Genomic Networks (11 papers)Gene Regulatory Network Analysis (6 papers)Microbial Metabolic Engineering and Bioproduction (3 papers)
- Partner nations
- GermanyUnited KingdomHungary
In The Last Decade
Dénes Türei
25 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 119
- Molecular Biology 1.5k
- Immunology 281
- Epidemiology 260
- Cancer Research 236
- Physiology 191
Countries citing papers authored by Dénes Türei
This map shows the geographic impact of Dénes Türei'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 Dénes Türei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dénes Türei more than expected).
Fields of papers citing papers by Dénes Türei
This network shows the impact of papers produced by Dénes Türei. 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 Dénes Türei. The network helps show where Dénes Türei may publish in the future.
Co-authorship network of co-authors of Dénes Türei
This figure shows the co-authorship network connecting the top 25 collaborators of Dénes Türei. A scholar is included among the top collaborators of Dénes Türei 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 Dénes Türei. Dénes Türei 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 | 1 | |
| 3 | 5 | |
| 4 | 91 | |
| 5 | 4 | |
| 6 | Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq databreakdown → | 237 |
| 7 | 16 | |
| 8 | 164 | |
| 9 | Benchmark and integration of resources for the estimation of human transcription factor activitiesbreakdown → | 483 |
| 10 | 28 | |
| 11 | 108 | |
| 12 | 4 | |
| 13 | OmniPath: guidelines and gateway for literature-curated signaling pathway resourcesbreakdown → | 386 |
| 14 | 21 | |
| 15 | 74 | |
| 16 | 89 | |
| 17 | 39 | |
| 18 | 79 | |
| 19 | 144 | |
| 20 | 87 |
About Dénes Türei
Dénes Türei is a scholar working on Biophysics, Molecular Biology and Geriatrics and Gerontology, having authored 25 papers that have together received 2.1k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (11 papers), Gene Regulatory Network Analysis (6 papers) and Microbial Metabolic Engineering and Bioproduction (3 papers). The work is most often cited by research in Molecular Biology (1.5k citations), Biophysics (117 citations) and Cancer Research (236 citations). Dénes Türei has collaborated with scholars based in Germany, United Kingdom and Hungary. Frequent co-authors include Julio Sáez-Rodríguez, Tamás Korcsmáros, Luz García‐Alonso, Mahmoud M. Ibrahim, Christian H. Holland, Dezső Módos, Péter Csermely, Katalin Lenti, Dávid Fazekas and Alberto Valdeolivas. Their work appears in journals such as Nucleic Acids Research, Nature Communications and Bioinformatics.
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.