Daniela Bakula
Impact in
- Aging top 5%
- Genetics, Aging, and Longevity in Model Organisms
- Physiology top 5%
- Calcium signaling and nucleotide metabolism
- Lysosomal Storage Disorders Research
- Telomeres, Telomerase, and Senescence
Papers in
-
- DNA Repair Mechanisms 4
- Epidemiology 10
- Autophagy in Disease and Therapy 10
- Co-authors
- Morten Scheibye‐Knudsen (13 shared papers)Tassula Proikas‐Cezanne (9 shared papers)Guido Keijzers (5 shared papers)Horst Robenek (3 shared papers)Tancred Frickey (2 shared papers)Mario P. Tschan (2 shared papers)Daniel Brigger (2 shared papers)Zsuzsanna Takács (2 shared papers)
- Journals
- Ageing Research Reviews (2 papers)Biochemical Society Transactions (2 papers)Autophagy (2 papers)Journal of Lipid Research (1 paper)Human Molecular Genetics (1 paper)
- Partner nations
- DenmarkGermanyUnited States
In The Last Decade
Daniela Bakula
21 papers receiving 963 citations
Peers
Comparison fields: 5 of 99
- Aging 59
- Physiology 83
- Epidemiology 470
- Cell Biology 232
- Geriatrics and Gerontology 31
Countries citing papers authored by Daniela Bakula
This map shows the geographic impact of Daniela Bakula'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 Daniela Bakula with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Bakula more than expected).
Fields of papers citing papers by Daniela Bakula
This network shows the impact of papers produced by Daniela Bakula. 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 Daniela Bakula. The network helps show where Daniela Bakula may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniela Bakula, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 160 | |
| 2 | 2022 | 123 | |
| 3 | 2020 | 121 | |
| 4 | 2010 | 112 | |
| 5 | 2013 | 85 | |
| 6 | 2012 | 81 | |
| 7 | 2018 | 54 | |
| 8 | 2014 | 52 | |
| 9 | 2017 | 47 | |
| 10 | 2022 | 32 | |
| 11 | 2012 | 26 | |
| 12 | 2017 | 21 | |
| 13 | 2013 | 13 | |
| 14 | 2020 | 10 | |
| 15 | 2018 | 9 | |
| 16 | 2014 | 8 | |
| 17 | 2024 | 8 | |
| 18 | 2022 | 7 | |
| 19 | 2024 | 5 | |
| 20 | 2025 | 2 |
About Daniela Bakula
Daniela Bakula is a scholar working on Molecular Biology, Epidemiology, Cell Biology, Physiology and Aging, having authored 23 papers that have together received 977 indexed citations. Recurring topics across this work include Autophagy in Disease and Therapy (10 papers), DNA Repair Mechanisms (4 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers), Endoplasmic Reticulum Stress and Disease (3 papers), Calcium signaling and nucleotide metabolism (3 papers), Cellular transport and secretion (3 papers), 3D Printing in Biomedical Research (3 papers) and Genetic factors in colorectal cancer (3 papers). The work is most often cited by research in Aging (59 citations), Physiology (83 citations), Epidemiology (470 citations), Cell Biology (232 citations) and Geriatrics and Gerontology (31 citations). Daniela Bakula has collaborated with scholars based in Denmark, Germany and United States. Frequent co-authors include Morten Scheibye‐Knudsen, Tassula Proikas‐Cezanne, Guido Keijzers, Horst Robenek, Tancred Frickey, Mario P. Tschan, Daniel Brigger, Zsuzsanna Takács, Garik V. Mkrtchyan and Brenna Osborne. Their work appears in journals such as Ageing Research Reviews, Biochemical Society Transactions, Autophagy, Journal of Lipid Research and Human Molecular Genetics.
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.