Jan Schröder
Impact in
- Molecular Biology top 10%
- Genomics and Phylogenetic Studies
- Pluripotent Stem Cells Research
- CRISPR and Genetic Engineering
- Renal and related cancers
- RNA and protein synthesis mechanisms
- Biophysics top 10%
Papers in
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- Genomics and Phylogenetic Studies 9
- Genomics and Chromatin Dynamics 2
- Developmental Biology and Gene Regulation 2
- Single-cell and spatial transcriptomics 2
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- T-cell and B-cell Immunology 3
- Co-authors
- Bertil Schmidt (4 shared papers)Yongchao Liu (2 shared papers)Leena Salmela (1 shared paper)Jose Maria Polo (8 shared papers)Heiko Schröder (2 shared papers)Ranjan Sinha (1 shared paper)Simon J. Puglisi (1 shared paper)Yichen Zhou (3 shared papers)
- Journals
- Bioinformatics (6 papers)PLoS ONE (4 papers)Science Immunology (2 papers)Scientific Reports (2 papers)BMC Bioinformatics (2 papers)
- Partner nations
- AustraliaUnited StatesGermany
In The Last Decade
Jan Schröder
42 papers receiving 1.3k citations
Jan Schröder's Hit Papers
Peers
Comparison fields: 5 of 134
- Molecular Biology 816
- Biophysics 39
- Immunology 123
- Structural Biology 9
- Cancer Research 75
Countries citing papers authored by Jan Schröder
This map shows the geographic impact of Jan Schröder'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 Jan Schröder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Schröder more than expected).
Fields of papers citing papers by Jan Schröder
This network shows the impact of papers produced by Jan Schröder. 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 Jan Schröder. The network helps show where Jan Schröder may publish in the future.
Co-authors
The 25 scholars most cited alongside Jan Schröder, 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 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Modelling human blastocysts by reprogramming fibroblasts into iBlastoids Hit paper breakdown → | 2021 | 261 |
| 2 | 2012 | 205 | |
| 3 | 2011 | 117 | |
| 4 | 2009 | 111 | |
| 5 | 2023 | 57 | |
| 6 | 2023 | 48 | |
| 7 | 2014 | 46 | |
| 8 | 2021 | 42 | |
| 9 | 2009 | 41 | |
| 10 | 2018 | 35 | |
| 11 | 2001 | 31 | |
| 12 | 2018 | 30 | |
| 13 | 2010 | 29 | |
| 14 | 2014 | 23 | |
| 15 | 2017 | 23 | |
| 16 | 2020 | 19 | |
| 17 | 2022 | 16 | |
| 18 | 2024 | 16 | |
| 19 | 2019 | 16 | |
| 20 | 2010 | 15 |
About Jan Schröder
Jan Schröder is a scholar working on Molecular Biology, Immunology, Cell Biology, Oncology and Hepatology, having authored 45 papers that have together received 1.3k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (9 papers), T-cell and B-cell Immunology (3 papers), CAR-T cell therapy research (2 papers), Plant Molecular Biology Research (2 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers), Genomics and Chromatin Dynamics (2 papers), Developmental Biology and Gene Regulation (2 papers) and Single-cell and spatial transcriptomics (2 papers). The work is most often cited by research in Molecular Biology (816 citations), Biophysics (39 citations), Immunology (123 citations), Structural Biology (9 citations) and Cancer Research (75 citations). Jan Schröder has collaborated with scholars based in Australia, United States and Germany. Frequent co-authors include Bertil Schmidt, Yongchao Liu, Leena Salmela, Jose Maria Polo, Heiko Schröder, Ranjan Sinha, Simon J. Puglisi, Yichen Zhou, Guizhi Sun and Anthony T. Papenfuss. Their work appears in journals such as Bioinformatics, PLoS ONE, Science Immunology, Scientific Reports and BMC 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.