Dezső Módos
Impact in
- Molecular Biology top 10%
- Bioinformatics and Genomic Networks
- Gut microbiota and health
- Genomics, phytochemicals, and oxidative stress
- Gene Regulatory Network Analysis
- Single-cell and spatial transcriptomics
- Gene expression and cancer classification
Papers in
-
- Bioinformatics and Genomic Networks 13
- Gut microbiota and health 5
- Single-cell and spatial transcriptomics 4
- Biomedical Text Mining and Ontologies 3
- Gene Regulatory Network Analysis 3
-
- Computational Drug Discovery Methods 6
- Co-authors
- Tamás Korcsmáros (27 shared papers)Dénes Türei (9 shared papers)Katalin Lenti (12 shared papers)Péter Csermely (10 shared papers)John P. Thomas (10 shared papers)Dávid Fazekas (9 shared papers)Lejla Gul (7 shared papers)Márton Ölbei (11 shared papers)
- Journals
- Scientific Reports (2 papers)npj Systems Biology and Applications (2 papers)Frontiers in Immunology (2 papers)Journal of Crohn s and Colitis (2 papers)Autophagy (2 papers)
- Partner nations
- United KingdomHungaryBelgium
In The Last Decade
Dezső Módos
36 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 117
- Molecular Biology 721
- Cancer Research 104
- Computational Theory and Mathematics 114
- Biophysics 33
- Aging 10
Countries citing papers authored by Dezső Módos
This map shows the geographic impact of Dezső Módos'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 Dezső Módos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dezső Módos more than expected).
Fields of papers citing papers by Dezső Módos
This network shows the impact of papers produced by Dezső Módos. 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 Dezső Módos. The network helps show where Dezső Módos may publish in the future.
Co-authors
The 25 scholars most cited alongside Dezső Módos, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 175 | |
| 2 | 2013 | 144 | |
| 3 | 2022 | 115 | |
| 4 | 2012 | 87 | |
| 5 | 2018 | 78 | |
| 6 | 2021 | 78 | |
| 7 | 2015 | 76 | |
| 8 | 2022 | 74 | |
| 9 | 2014 | 44 | |
| 10 | 2013 | 39 | |
| 11 | 2013 | 28 | |
| 12 | 2015 | 21 | |
| 13 | 2017 | 20 | |
| 14 | 2020 | 19 | |
| 15 | 2022 | 18 | |
| 16 | 2021 | 13 | |
| 17 | 2021 | 12 | |
| 18 | 2020 | 10 | |
| 19 | 2016 | 7 | |
| 20 | 2021 | 7 |
About Dezső Módos
Dezső Módos is a scholar working on Molecular Biology, Computational Theory and Mathematics, Genetics, Cancer Research and Oncology, having authored 38 papers that have together received 1.1k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (13 papers), Computational Drug Discovery Methods (6 papers), Gut microbiota and health (5 papers), Inflammatory Bowel Disease (5 papers), Single-cell and spatial transcriptomics (4 papers), MicroRNA in disease regulation (3 papers), Biomedical Text Mining and Ontologies (3 papers) and Gene Regulatory Network Analysis (3 papers). The work is most often cited by research in Molecular Biology (721 citations), Cancer Research (104 citations), Computational Theory and Mathematics (114 citations), Biophysics (33 citations) and Aging (10 citations). Dezső Módos has collaborated with scholars based in United Kingdom, Hungary and Belgium. Frequent co-authors include Tamás Korcsmáros, Dénes Türei, Katalin Lenti, Péter Csermely, John P. Thomas, Dávid Fazekas, Lejla Gul, Márton Ölbei, Simon Rushbrook and Nick Powell. Their work appears in journals such as Scientific Reports, npj Systems Biology and Applications, Frontiers in Immunology, Journal of Crohn s and Colitis and Autophagy.
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.