Jan Schröder
Impact in
- Molecular Biology top 10%
- Genomics and Phylogenetic Studies
- Pluripotent Stem Cells Research
- CRISPR and Genetic Engineering
- Renal and related cancers
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- Cancer Genomics and Diagnostics
Papers in
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- Genomics and Phylogenetic Studies 8
- Single-cell and spatial transcriptomics 2
- Developmental Biology and Gene Regulation 2
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- T-cell and B-cell Immunology 3
- Immune cells in cancer 2
- Co-authors
- Bertil Schmidt (4 shared papers)Yongchao Liu (2 shared papers)Leena Salmela (1 shared paper)Anthony T. Papenfuss (10 shared papers)Alexander Dobrovic (1 shared paper)Hongdo Do (1 shared paper)Terence P. Speed (1 shared paper)Jocelyn Sietsma Penington (1 shared paper)
- Journals
- Bioinformatics (6 papers)PLoS ONE (4 papers)BMC Bioinformatics (2 papers)Science Immunology (2 papers)Scientific Reports (2 papers)
- Partner nations
- AustraliaUnited StatesGermany
In The Last Decade
Jan Schröder
40 papers receiving 1.4k citations
Jan Schröder's Hit Papers
Peers
Comparison fields: 5 of 135
- Molecular Biology 861
- Cancer Research 124
- Genetics 188
- Biophysics 37
- Immunology 127
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 43 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 | 246 |
| 2 | 2012 | 199 | |
| 3 | 2017 | 191 | |
| 4 | 2011 | 110 | |
| 5 | 2009 | 105 | |
| 6 | 2023 | 49 | |
| 7 | 2014 | 47 | |
| 8 | 2023 | 44 | |
| 9 | 2021 | 41 | |
| 10 | 2009 | 38 | |
| 11 | 2018 | 33 | |
| 12 | 2010 | 32 | |
| 13 | 2018 | 29 | |
| 14 | 2001 | 28 | |
| 15 | 2014 | 22 | |
| 16 | 2017 | 21 | |
| 17 | 2020 | 19 | |
| 18 | 2019 | 15 | |
| 19 | 2010 | 15 | |
| 20 | 2022 | 15 |
About Jan Schröder
Jan Schröder is a scholar working on Molecular Biology, Immunology, Cell Biology, Oncology and Plant Science, having authored 43 papers that have together received 1.4k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (8 papers), T-cell and B-cell Immunology (3 papers), Microtubule and mitosis dynamics (2 papers), Single-cell and spatial transcriptomics (2 papers), Immune cells in cancer (2 papers), Developmental Biology and Gene Regulation (2 papers), Hippo pathway signaling and YAP/TAZ (2 papers) and Plant Molecular Biology Research (2 papers). The work is most often cited by research in Molecular Biology (861 citations), Cancer Research (124 citations), Genetics (188 citations), Biophysics (37 citations) and Immunology (127 citations). Jan Schröder has collaborated with scholars based in Australia, United States and Germany. Frequent co-authors include Bertil Schmidt, Yongchao Liu, Leena Salmela, Anthony T. Papenfuss, Alexander Dobrovic, Hongdo Do, Terence P. Speed, Jocelyn Sietsma Penington, Ramyar Molania and Daniel Cameron. Their work appears in journals such as Bioinformatics, PLoS ONE, BMC Bioinformatics, Science Immunology and Scientific Reports.
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.