Daniel Schramek

6.9k total citations
50 papers, 2.9k citations indexed

About

Daniel Schramek is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Daniel Schramek has authored 50 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 17 papers in Oncology and 9 papers in Cancer Research. Recurrent topics in Daniel Schramek's work include CRISPR and Genetic Engineering (9 papers), Cancer Genomics and Diagnostics (6 papers) and Cancer-related Molecular Pathways (5 papers). Daniel Schramek is often cited by papers focused on CRISPR and Genetic Engineering (9 papers), Cancer Genomics and Diagnostics (6 papers) and Cancer-related Molecular Pathways (5 papers). Daniel Schramek collaborates with scholars based in Canada, United States and Austria. Daniel Schramek's co-authors include Josef Penninger, Verena Sigl, Elaine Fuchs, Reiko Hanada, J. Andrew Pospisilik, Ataman Sendoel, Andreas Leibbrandt, Roger J. Daly, Rama Khokha and Christopher J. Ormandy and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Daniel Schramek

50 papers receiving 2.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Schramek Canada 25 1.9k 939 483 407 304 50 2.9k
Raj Chari United States 36 3.2k 1.7× 603 0.6× 816 1.7× 348 0.9× 473 1.6× 98 4.2k
Xueyi Dong China 35 2.7k 1.5× 829 0.9× 1.3k 2.7× 345 0.8× 318 1.0× 79 3.7k
William Damsky United States 32 1.9k 1.0× 1.6k 1.7× 335 0.7× 1.4k 3.5× 451 1.5× 122 4.7k
Tae Jin Kim South Korea 29 1.1k 0.6× 515 0.5× 257 0.5× 698 1.7× 169 0.6× 122 2.6k
Christopher D. Scharer United States 28 1.3k 0.7× 474 0.5× 316 0.7× 1.4k 3.4× 153 0.5× 91 2.7k
Roman Szabo United States 32 1.6k 0.9× 453 0.5× 668 1.4× 410 1.0× 176 0.6× 55 3.5k
Lars Uhlin‐Hansen Norway 27 1.1k 0.6× 688 0.7× 713 1.5× 575 1.4× 130 0.4× 56 2.5k
David E. Solow-Cordero United States 18 1.6k 0.8× 314 0.3× 418 0.9× 133 0.3× 130 0.4× 30 2.3k
Luigi Bagella United States 29 1.7k 0.9× 736 0.8× 261 0.5× 267 0.7× 270 0.9× 70 2.5k
Mariëlle van Gijn Netherlands 22 2.6k 1.4× 1.4k 1.4× 349 0.7× 791 1.9× 271 0.9× 55 4.3k

Countries citing papers authored by Daniel Schramek

Since Specialization
Citations

This map shows the geographic impact of Daniel Schramek'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 Daniel Schramek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Schramek more than expected).

Fields of papers citing papers by Daniel Schramek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Schramek. 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 Daniel Schramek. The network helps show where Daniel Schramek may publish in the future.

Co-authorship network of co-authors of Daniel Schramek

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Schramek. A scholar is included among the top collaborators of Daniel Schramek 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 Daniel Schramek. Daniel Schramek 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.
Ragotte, Robert J., John Kit Chung Tam, Jacob M. Berman, et al.. (2025). De novo design of potent inhibitors of clostridial family toxins. Proceedings of the National Academy of Sciences. 122(39). e2509329122–e2509329122. 1 indexed citations
2.
Chen, Danian, Suying Lü, Katherine Huang, et al.. (2025). Cell cycle duration determines oncogenic transformation capacity. Nature. 641(8065). 1309–1318. 3 indexed citations
3.
Poirson, Juline, Hanna Cho, Mandy Hiu Yi Lam, et al.. (2024). Proteome-scale discovery of protein degradation and stabilization effectors. Nature. 628(8009). 878–886. 29 indexed citations
4.
Jenkins, Robert B., et al.. (2024). Switching Drivers: Epigenetic Rewiring to Genetic Progression in Glioma. Cancer Research. 85(5). 836–837. 1 indexed citations
5.
MacLeod, Graham, Sichun Lin, Michelle Kushida, et al.. (2024). Fitness Screens Map State-Specific Glioblastoma Stem Cell Vulnerabilities. Cancer Research. 84(23). 3967–3983. 3 indexed citations
6.
Uijttewaal, Esther C. H., Joonsun Lee, Gintautas Vainorius, et al.. (2024). CRISPR-StAR enables high-resolution genetic screening in complex in vivo models. Nature Biotechnology. 43(11). 1848–1860. 11 indexed citations
7.
Cheng, Kevin, et al.. (2023). Mutational processes of tobacco smoking and APOBEC activity generate protein-truncating mutations in cancer genomes. Science Advances. 9(44). eadh3083–eadh3083. 5 indexed citations
8.
Malik, Ahmad, Dzana Dervovic, Ricky Tsai, et al.. (2023). The NOTCH-RIPK4-IRF6-ELOVL4 Axis Suppresses Squamous Cell Carcinoma. Cancers. 15(3). 737–737. 14 indexed citations
9.
Hesketh, Geoffrey G., Judy Pawling, Dushyandi Rajendran, et al.. (2020). The GATOR–Rag GTPase pathway inhibits mTORC1 activation by lysosome-derived amino acids. Science. 370(6514). 351–356. 51 indexed citations
10.
Lee, Hunsang, Greg L. Beilhartz, Iga Kucharska, et al.. (2020). Recognition of Semaphorin Proteins by P. sordellii Lethal Toxin Reveals Principles of Receptor Specificity in Clostridial Toxins. Cell. 182(2). 345–356.e16. 32 indexed citations
11.
Loganathan, Sampath K., Ahmad Malik, Ellen Langille, Chen Luxenburg, & Daniel Schramek. (2020). In Vivo CRISPR/Cas9 Screening to Simultaneously Evaluate Gene Function in Mouse Skin and Oral Cavity. Journal of Visualized Experiments. 2 indexed citations
12.
Schramek, Daniel, Ataman Sendoel, Jeremy P. Segal, et al.. (2014). Direct in Vivo RNAi Screen Unveils Myosin IIa as a Tumor Suppressor of Squamous Cell Carcinomas. Science. 343(6168). 309–313. 212 indexed citations
13.
Halbach, Sebastian, Konrad Aumann, Sven Schwemmers, et al.. (2012). Gab2 signaling in chronic myeloid leukemia cells confers resistance to multiple Bcr-Abl inhibitors. Leukemia. 27(1). 118–129. 42 indexed citations
14.
Schramek, Daniel, et al.. (2012). RANK und RANKL - Vom Knochen zum Mammakarzinom. 19(1). 27–32. 1 indexed citations
15.
Elling, Ulrich, Jasmin Taubenschmid, Gerald Wirnsberger, et al.. (2011). Forward and Reverse Genetics through Derivation of Haploid Mouse Embryonic Stem Cells. Cell stem cell. 9(6). 563–574. 187 indexed citations
16.
Schramek, Daniel, Verena Sigl, & Josef Penninger. (2011). RANKL and RANK in sex hormone-induced breast cancer and breast cancer metastasis. Trends in Endocrinology and Metabolism. 22(5). 188–194. 46 indexed citations
17.
Schramek, Daniel, Athanassios Kotsinas, Arabella Meixner, et al.. (2011). The stress kinase MKK7 couples oncogenic stress to p53 stability and tumor suppression. Nature Genetics. 43(3). 212–219. 76 indexed citations
18.
Cronin, Shane J. F., Nadine T. Nehme, Samuel Liégeois, et al.. (2009). Genome-Wide RNAi Screen Identifies Genes Involved in Intestinal Pathogenic Bacterial Infection. Science. 325(5938). 340–343. 245 indexed citations
19.
Brummer, Tilman, Mark Larance, Paul Timpson, et al.. (2009). The docking protein and proto-oncogene product Gab2 is regulated via a novel negative feedback mechanism mediated by 14-3-3 binding. Cell Communication and Signaling. 7(S1). 4 indexed citations
20.
Brummer, Tilman, Mark Larance, Maria Teresa Herrera Abreu, et al.. (2008). Phosphorylation‐dependent binding of 14‐3‐3 terminates signalling by the Gab2 docking protein. The EMBO Journal. 27(17). 2305–2316. 47 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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