Dagmar Iber
Impact in
- Immunology top 5%
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Immunotherapy and Immune Responses
- Cell Biology top 5%
- Cellular Mechanics and Interactions
Papers in
-
- Developmental Biology and Gene Regulation 25
- Renal and related cancers 9
- Gene Regulatory Network Analysis 8
- Pluripotent Stem Cells Research 7
- Cell Biology 22
- Cellular Mechanics and Interactions 14
- Hippo pathway signaling and YAP/TAZ 9
- Co-authors
- Michael S. Neuberger (1 shared paper)Facundo D. Batista (1 shared paper)Denis Menshykau (10 shared papers)Philip K. Maini (2 shared papers)Conradin Kraemer (3 shared papers)Roman Vetter (16 shared papers)Michael Meyer‐Hermann (1 shared paper)Marcelo Boareto (6 shared papers)
- Journals
- Development (10 papers)Scientific Reports (5 papers)Cell Reports (3 papers)Nature Communications (3 papers)Bioinformatics (2 papers)
- Partner nations
- SwitzerlandUnited KingdomUnited States
In The Last Decade
Dagmar Iber
80 papers receiving 2.2k citations
Dagmar Iber's Hit Papers
Peers
Comparison fields: 5 of 133
- Immunology 551
- Cell Biology 420
- Developmental Neuroscience 80
- Molecular Biology 1.1k
- Aging 28
Countries citing papers authored by Dagmar Iber
This map shows the geographic impact of Dagmar Iber'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 Dagmar Iber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dagmar Iber more than expected).
Fields of papers citing papers by Dagmar Iber
This network shows the impact of papers produced by Dagmar Iber. 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 Dagmar Iber. The network helps show where Dagmar Iber may publish in the future.
Co-authors
The 25 scholars most cited alongside Dagmar Iber, 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 83 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | B cells acquire antigen from target cells after synapse formation Hit paper breakdown → | 2001 | 516 |
| 2 | 2013 | 109 | |
| 3 | 2006 | 103 | |
| 4 | 2011 | 84 | |
| 5 | 2012 | 82 | |
| 6 | 2015 | 81 | |
| 7 | 2019 | 73 | |
| 8 | 2014 | 65 | |
| 9 | 2012 | 60 | |
| 10 | 2019 | 56 | |
| 11 | 2017 | 49 | |
| 12 | 2017 | 48 | |
| 13 | 2014 | 47 | |
| 14 | 2006 | 45 | |
| 15 | 2021 | 44 | |
| 16 | 2020 | 39 | |
| 17 | 2015 | 36 | |
| 18 | 2024 | 32 | |
| 19 | 2023 | 31 | |
| 20 | 2002 | 29 |
About Dagmar Iber
Dagmar Iber is a scholar working on Molecular Biology, Cell Biology, Genetics, Oncology and Pulmonary and Respiratory Medicine, having authored 83 papers that have together received 2.2k indexed citations. Recurring topics across this work include Developmental Biology and Gene Regulation (25 papers), Cellular Mechanics and Interactions (14 papers), Cancer Cells and Metastasis (11 papers), Renal and related cancers (9 papers), Hippo pathway signaling and YAP/TAZ (9 papers), Gene Regulatory Network Analysis (8 papers), Pluripotent Stem Cells Research (7 papers) and Genetic and Kidney Cyst Diseases (6 papers). The work is most often cited by research in Immunology (551 citations), Cell Biology (420 citations), Developmental Neuroscience (80 citations), Molecular Biology (1.1k citations) and Aging (28 citations). Dagmar Iber has collaborated with scholars based in Switzerland, United Kingdom and United States. Frequent co-authors include Michael S. Neuberger, Facundo D. Batista, Denis Menshykau, Philip K. Maini, Conradin Kraemer, Roman Vetter, Michael Meyer‐Hermann, Marcelo Boareto, Verdon Taylor and Fernando Casares. Their work appears in journals such as Development, Scientific Reports, Cell Reports, 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.