Daniela Hartl
Impact in
- Physiology top 10%
- Alzheimer's disease research and treatments
Papers in
-
- Mitochondrial Function and Pathology 4
- Ubiquitin and proteasome pathways 3
- RNA Research and Splicing 3
- Bioinformatics and Genomic Networks 3
- Gene expression and cancer classification 2
-
- Alzheimer's disease research and treatments 7
- Co-authors
- Joachim Klose (13 shared papers)Michael Rohe (9 shared papers)Claus Zabel (11 shared papers)Lei Mao (9 shared papers)Thomas E. Willnow (3 shared papers)Sabrina Pichler (5 shared papers)Manuel Mayhaus (5 shared papers)Wei Gu (3 shared papers)
- Journals
- Journal of Proteome Research (6 papers)PLoS ONE (5 papers)PROTEOMICS (4 papers)Journal of Alzheimer s Disease (1 paper)Journal of Neuroscience (1 paper)
- Partner nations
- GermanyLuxembourgUnited States
In The Last Decade
Daniela Hartl
27 papers receiving 675 citations
Peers
Comparison fields: 5 of 96
- Biological Psychiatry 22
- Physiology 216
- Cellular and Molecular Neuroscience 145
- Aging 14
- Neurology 55
Countries citing papers authored by Daniela Hartl
This map shows the geographic impact of Daniela Hartl'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 Hartl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Hartl more than expected).
Fields of papers citing papers by Daniela Hartl
This network shows the impact of papers produced by Daniela Hartl. 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 Hartl. The network helps show where Daniela Hartl may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniela Hartl, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 102 | |
| 2 | 2013 | 79 | |
| 3 | 2008 | 62 | |
| 4 | 2008 | 50 | |
| 5 | 2018 | 49 | |
| 6 | 2010 | 33 | |
| 7 | 2012 | 30 | |
| 8 | 2012 | 30 | |
| 9 | 2013 | 29 | |
| 10 | 2013 | 28 | |
| 11 | 2008 | 26 | |
| 12 | 2008 | 21 | |
| 13 | 2008 | 21 | |
| 14 | 2007 | 20 | |
| 15 | 2008 | 14 | |
| 16 | 2010 | 12 | |
| 17 | 2016 | 11 | |
| 18 | 2018 | 11 | |
| 19 | 2015 | 10 | |
| 20 | 2015 | 9 |
About Daniela Hartl
Daniela Hartl is a scholar working on Molecular Biology, Physiology, Cellular and Molecular Neuroscience, Cell Biology and Spectroscopy, having authored 27 papers that have together received 682 indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (7 papers), Genetic Neurodegenerative Diseases (4 papers), Mitochondrial Function and Pathology (4 papers), Advanced Proteomics Techniques and Applications (3 papers), Ubiquitin and proteasome pathways (3 papers), RNA Research and Splicing (3 papers), Bioinformatics and Genomic Networks (3 papers) and Gene expression and cancer classification (2 papers). The work is most often cited by research in Biological Psychiatry (22 citations), Physiology (216 citations), Cellular and Molecular Neuroscience (145 citations), Aging (14 citations) and Neurology (55 citations). Daniela Hartl has collaborated with scholars based in Germany, Luxembourg and United States. Frequent co-authors include Joachim Klose, Michael Rohe, Claus Zabel, Lei Mao, Thomas E. Willnow, Sabrina Pichler, Manuel Mayhaus, Wei Gu, Gilles Gasparoni and Andreas Keller. Their work appears in journals such as Journal of Proteome Research, PLoS ONE, PROTEOMICS, Journal of Alzheimer s Disease and Journal of Neuroscience.
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.