Daniel Speidel

1.8k total citations
18 papers, 1.4k citations indexed

About

Daniel Speidel is a scholar working on Molecular Biology, Oncology and Biotechnology. According to data from OpenAlex, Daniel Speidel has authored 18 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 13 papers in Oncology and 4 papers in Biotechnology. Recurrent topics in Daniel Speidel's work include Cancer-related Molecular Pathways (13 papers), Cell death mechanisms and regulation (6 papers) and Ubiquitin and proteasome pathways (5 papers). Daniel Speidel is often cited by papers focused on Cancer-related Molecular Pathways (13 papers), Cell death mechanisms and regulation (6 papers) and Ubiquitin and proteasome pathways (5 papers). Daniel Speidel collaborates with scholars based in Germany, Australia and United Kingdom. Daniel Speidel's co-authors include Wolfgang Deppert, Sonja Wolff, Ute M. Moll, Christina Heinlein, Martin Michaelis, Jindřich Činátl, Jürgen Löhler, Florian Rothweiler, Franz Rödel and Rainer Breitling and has published in prestigious journals such as Cancer Research, Oncogene and Current Opinion in Cell Biology.

In The Last Decade

Daniel Speidel

18 papers receiving 1.4k 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 Speidel Germany 15 971 630 250 126 119 18 1.4k
A. Pieter J. van den Heuvel United States 13 967 1.0× 363 0.6× 335 1.3× 160 1.3× 130 1.1× 14 1.4k
Larissa S. Agapova Russia 15 1.2k 1.3× 608 1.0× 354 1.4× 174 1.4× 112 0.9× 24 1.7k
J. E. Kravchenko Russia 10 1.0k 1.1× 563 0.9× 356 1.4× 93 0.7× 101 0.8× 17 1.5k
Masahito Hanada Japan 8 1.2k 1.2× 487 0.8× 235 0.9× 138 1.1× 87 0.7× 12 1.6k
Jong Kuk Park South Korea 25 1.2k 1.2× 552 0.9× 365 1.5× 130 1.0× 85 0.7× 53 1.8k
Sonja Wolff Germany 11 1.4k 1.5× 603 1.0× 451 1.8× 205 1.6× 122 1.0× 13 1.8k
Shing Leng Chan Singapore 22 977 1.0× 375 0.6× 258 1.0× 152 1.2× 82 0.7× 33 1.4k
Helena L. Borges Brazil 20 771 0.8× 333 0.5× 176 0.7× 92 0.7× 85 0.7× 40 1.2k
Xiangao Sun United States 12 1.3k 1.3× 497 0.8× 224 0.9× 133 1.1× 57 0.5× 13 1.6k
Baskaran Rajasekaran United States 20 1.6k 1.6× 552 0.9× 305 1.2× 196 1.6× 68 0.6× 25 2.1k

Countries citing papers authored by Daniel Speidel

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Speidel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Speidel

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Speidel. A scholar is included among the top collaborators of Daniel Speidel 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 Speidel. Daniel Speidel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Antczak, Magdalena, Nina Weiler, Florian Rothweiler, et al.. (2025). Using a novel panel of drug-resistant triple-negative breast cancer cell lines to identify candidate therapeutic targets and biomarkers. Cancer Letters. 624. 217754–217754. 1 indexed citations
2.
Speidel, Daniel, et al.. (2017). RUNX1 Upregulation by Cytotoxic Drugs Promotes Apoptosis. Cancer Research. 77(24). 6818–6824. 6 indexed citations
3.
Speidel, Daniel. (2015). The role of DNA damage responses in p53 biology. Archives of Toxicology. 89(4). 501–517. 137 indexed citations
4.
Slatter, Tania L., Noelyn Hung, Heather Campbell, et al.. (2015). Δ122p53, a mouse model of Δ133p53α, enhances the tumor-suppressor activities of an attenuated p53 mutant. Cell Death and Disease. 6(6). e1783–e1783. 22 indexed citations
5.
Činátl, Jindřich, Daniel Speidel, Ian R. Hardcastle, & Martin Michaelis. (2014). Resistance acquisition to MDM2 inhibitors. Biochemical Society Transactions. 42(4). 752–757. 22 indexed citations
6.
Chircop, Megan & Daniel Speidel. (2014). Cellular Stress Responses in Cancer and Cancer Therapy. Frontiers in Oncology. 4. 304–304. 16 indexed citations
7.
Michaelis, Martin, Florian Rothweiler, Susanne Barth, et al.. (2012). Human neuroblastoma cells with acquired resistance to the p53 activator RITA retain functional p53 and sensitivity to other p53 activating agents. Cell Death and Disease. 3(4). e294–e294. 19 indexed citations
8.
Michaelis, Martin, Florian Rothweiler, Susanne Barth, et al.. (2011). Adaptation of cancer cells from different entities to the MDM2 inhibitor nutlin-3 results in the emergence of p53-mutated multi-drug-resistant cancer cells. Cell Death and Disease. 2(12). e243–e243. 149 indexed citations
9.
Heinlein, Christina & Daniel Speidel. (2011). High‐Resolution Cell Cycle and DNA Ploidy Analysis in Tissue Samples. Current Protocols in Cytometry. 56(1). 7.39.1–7.39.11. 8 indexed citations
10.
Rübsam, Anne, C. Schmitz-Salue, Gabriele Warnecke, et al.. (2010). Chloroquine activates the p53 pathway and induces apoptosis in human glioma cells. Neuro-Oncology. 12(4). 389–400. 119 indexed citations
11.
Heinlein, Christina, Wolfgang Deppert, Antony W. Braithwaite, & Daniel Speidel. (2010). A rapid and optimization-free procedure allows the in vivo detection of subtle cell cycle and ploidy alterations in tissues by flow cytometry. Cell Cycle. 9(17). 3584–3590. 24 indexed citations
12.
Speidel, Daniel. (2009). Transcription-independent p53 apoptosis: an alternative route to death. Trends in Cell Biology. 20(1). 14–24. 291 indexed citations
13.
Heinlein, Christina, et al.. (2007). Mutant p53R270H gain of function phenotype in a mouse model for oncogene‐induced mammary carcinogenesis. International Journal of Cancer. 122(8). 1701–1709. 53 indexed citations
14.
Engelmann, Afra, Daniel Speidel, Georg W. Bornkamm, Wolfgang Deppert, & Carol Stocking. (2007). Gadd45β is a pro-survival factor associated with stress-resistant tumors. Oncogene. 27(10). 1429–1438. 32 indexed citations
15.
Moll, Ute M., Sonja Wolff, Daniel Speidel, & Wolfgang Deppert. (2005). Transcription-independent pro-apoptotic functions of p53. Current Opinion in Cell Biology. 17(6). 631–636. 389 indexed citations
16.
Stöter, Martin, Ana‐Maria Bamberger, Daniel Speidel, et al.. (2005). Inhibition of casein kinase I delta alters mitotic spindle formation and induces apoptosis in trophoblast cells. Oncogene. 24(54). 7964–7975. 48 indexed citations
17.
Speidel, Daniel, et al.. (2005). Dissection of transcriptional and non-transcriptional p53 activities in the response to genotoxic stress. Oncogene. 25(6). 940–953. 64 indexed citations
18.
Will, Elke, Daniel Speidel, Zheng Wang, et al.. (2005). HOXB4 Inhibits Cell Growth in a Dose-Dependent Manner and Sensitizes Cells Towards Extrinsic Cues. Cell Cycle. 5(1). 14–22. 16 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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