Jan Schröder

3.3k total citations · 1 hit paper
37 papers, 1.3k citations indexed

About

Jan Schröder is a scholar working on Molecular Biology, Cell Biology and Plant Science. According to data from OpenAlex, Jan Schröder has authored 37 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 6 papers in Cell Biology and 6 papers in Plant Science. Recurrent topics in Jan Schröder's work include Genomics and Phylogenetic Studies (11 papers), Genomic variations and chromosomal abnormalities (4 papers) and Pluripotent Stem Cells Research (3 papers). Jan Schröder is often cited by papers focused on Genomics and Phylogenetic Studies (11 papers), Genomic variations and chromosomal abnormalities (4 papers) and Pluripotent Stem Cells Research (3 papers). Jan Schröder collaborates with scholars based in Australia, Germany and United States. Jan Schröder's co-authors include Bertil Schmidt, Yongchao Liu, Leena Salmela, Anthony T. Papenfuss, Daniel Cameron, Ramyar Molania, Hongdo Do, Terence P. Speed, Alexander Dobrovic and Jocelyn Sietsma Penington and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Journal of Neuroscience.

In The Last Decade

Jan Schröder

34 papers receiving 1.3k citations

Hit Papers

Modelling human blastocysts by reprogramming fibroblasts ... 2021 2026 2022 2024 2021 50 100 150 200

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jan Schröder Australia 17 893 201 185 141 134 37 1.3k
Tatyana Goldberg Germany 15 1.1k 1.2× 186 0.9× 150 0.8× 52 0.4× 102 0.8× 22 1.7k
Mary Mangan United States 10 1.1k 1.2× 247 1.2× 167 0.9× 84 0.6× 135 1.0× 13 1.6k
Justin Chu Canada 17 1.3k 1.4× 286 1.4× 356 1.9× 86 0.6× 108 0.8× 33 1.8k
Florian Hahne United States 10 1.1k 1.3× 201 1.0× 112 0.6× 57 0.4× 153 1.1× 17 1.6k
Luka A. Clarke Portugal 21 752 0.8× 172 0.9× 130 0.7× 54 0.4× 51 0.4× 51 1.5k
Botond Sipos United Kingdom 14 1.3k 1.4× 194 1.0× 64 0.3× 180 1.3× 211 1.6× 20 1.9k
Luis Mendoza Mexico 25 1.5k 1.7× 249 1.2× 363 2.0× 64 0.5× 156 1.2× 63 2.4k
Evelyn Camon United Kingdom 16 1.5k 1.6× 175 0.9× 211 1.1× 194 1.4× 84 0.6× 19 2.0k
Benjamin W. Pruitt United States 8 2.0k 2.2× 295 1.5× 140 0.8× 65 0.5× 68 0.5× 9 2.1k
Hamed S. Najafabadi Canada 23 2.1k 2.4× 357 1.8× 170 0.9× 104 0.7× 396 3.0× 64 2.8k

Countries citing papers authored by Jan Schröder

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Jan Schröder

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Schröder. A scholar is included among the top collaborators of Jan Schröder based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jan Schröder. Jan Schröder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Schröder, Jan, et al.. (2025). Pareto‐Optimal Treatment of Uncertainties in Model‐Based Process Design and Operation. Chemie Ingenieur Technik. 97(11-12). 1057–1064.
2.
Lonsdale, Andrew, et al.. (2024). Damsel: analysis and visualisation of DamID sequencing in R. Bioinformatics. 40(12).
3.
Chang, Jessie J.‐Y., Samantha L. Grimley, Georgia Deliyannis, et al.. (2024). Uncovering strain- and age-dependent innate immune responses to SARS-CoV-2 infection in air-liquid-interface cultured nasal epithelia. iScience. 27(6). 110009–110009. 1 indexed citations
4.
Schröder, Jan, Anne M. Kong, Adrian Fox, et al.. (2024). Liver specification of human iPSC-derived endothelial cells transplanted into mouse liver. JHEP Reports. 6(5). 101023–101023. 4 indexed citations
5.
Zhou, Jerry, Xiaodong Liu, Jan Schröder, et al.. (2023). Transcriptome and Proteome Profiling of Primary Human Gastric Interstitial Cells of Cajal Predicts Pacemaker Networks. Journal of Neurogastroenterology and Motility. 29(2). 238–249. 2 indexed citations
6.
Schröder, Jan, et al.. (2023). Tribological Properties of Lipss on Inconel 718 and Stellite Alloys. SSRN Electronic Journal.
7.
Leinenga, Gerhard, Liviu‐Gabriel Bodea, Jan Schröder, et al.. (2022). Transcriptional signature in microglia isolated from an Alzheimer's disease mouse model treated with scanning ultrasound. Bioengineering & Translational Medicine. 8(1). e10329–e10329. 13 indexed citations
8.
Liu, Xiaodong, Jia Ping Tan, Jan Schröder, et al.. (2021). Modelling human blastocysts by reprogramming fibroblasts into iBlastoids. Nature. 591(7851). 627–632. 240 indexed citations breakdown →
9.
Bediaga, Naiara G., Hannah D. Coughlan, Timothy M. Johanson, et al.. (2021). Multi-level remodelling of chromatin underlying activation of human T cells. Scientific Reports. 11(1). 528–528. 38 indexed citations
10.
Busuttil, Rita A., David S. Liu, Natasha Di Costanzo, et al.. (2018). An orthotopic mouse model of gastric cancer invasion and metastasis. Scientific Reports. 8(1). 825–825. 33 indexed citations
11.
Vissers, Joseph H.A., Francesca Froldi, Jan Schröder, et al.. (2018). The Scalloped and Nerfin-1 Transcription Factors Cooperate to Maintain Neuronal Cell Fate. Cell Reports. 25(6). 1561–1576.e7. 29 indexed citations
12.
Cameron, Daniel, Jan Schröder, Jocelyn Sietsma Penington, et al.. (2017). GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly. Genome Research. 27(12). 2050–2060. 182 indexed citations
13.
McCoy, J. Michael, Rebecca J. Stewart, Alessandro D. Uboldi, et al.. (2017). A forward genetic screen identifies a negative regulator of rapid Ca2+-dependent cell egress (MS1) in the intracellular parasite Toxoplasma gondii. Journal of Biological Chemistry. 292(18). 7662–7674. 21 indexed citations
14.
Schröder, Jan, Adrianto Wirawan, Bertil Schmidt, & Anthony T. Papenfuss. (2017). CLOVE: classification of genomic fusions into structural variation events. BMC Bioinformatics. 18(1). 346–346. 7 indexed citations
15.
Yong, Carmen S., Jennifer A. Westwood, Jan Schröder, et al.. (2015). Expression of a Chimeric Antigen Receptor in Multiple Leukocyte Lineages in Transgenic Mice. PLoS ONE. 10(10). e0140543–e0140543. 8 indexed citations
16.
Wirawan, Adrianto, Robert S. Harris, Yongchao Liu, Bertil Schmidt, & Jan Schröder. (2014). HECTOR: a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data. BMC Bioinformatics. 15(1). 131–131. 22 indexed citations
17.
Schröder, Jan, Hélène A Benink, Marcus Dyba, & Georgyi V. Los. (2009). In Vivo Labeling Method Using a Genetic Construct for Nanoscale Resolution Microscopy. Biophysical Journal. 96(1). L1–L3. 38 indexed citations
18.
Schröder, Jan, et al.. (2008). BMA - Boolean matrices as model for motif kernels. RMIT Research Repository (RMIT University Library). 36–41. 2 indexed citations
19.
Schröder, Jan, et al.. (2007). Topic Trend Detection in Newsgroups.. 21(3). 37–40. 3 indexed citations
20.
Schröder, Jan, et al.. (1995). Anfangsgründe des Naturrechts (Elementa iuris naturae). 2 indexed citations

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.

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