Alexander Loewer

12.9k total citations · 2 hit papers
43 papers, 9.5k citations indexed

About

Alexander Loewer is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Alexander Loewer has authored 43 papers receiving a total of 9.5k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 24 papers in Oncology and 11 papers in Cell Biology. Recurrent topics in Alexander Loewer's work include Cancer-related Molecular Pathways (20 papers), DNA Repair Mechanisms (10 papers) and Microtubule and mitosis dynamics (7 papers). Alexander Loewer is often cited by papers focused on Cancer-related Molecular Pathways (20 papers), DNA Repair Mechanisms (10 papers) and Microtubule and mitosis dynamics (7 papers). Alexander Loewer collaborates with scholars based in Germany, United States and Australia. Alexander Loewer's co-authors include Galit Lahav, Lea H. Gregersen, Mathias Munschauer, Markus Landthaler, Sebastian Memczak, Marvin Jens, Christine Kocks, Ferdinand le Noble, Nikolaus Rajewsky and Ulrike Ziebold and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Alexander Loewer

42 papers receiving 9.5k citations

Hit Papers

Circular RNAs are a large class of animal RNAs with regul... 2012 2026 2016 2021 2013 2012 2.0k 4.0k 6.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alexander Loewer Germany 24 8.8k 5.6k 1.3k 578 386 43 9.5k
Stefan Hüttelmaier Germany 49 6.6k 0.7× 2.9k 0.5× 695 0.5× 1.1k 1.8× 433 1.1× 112 8.3k
Aimee L. Jackson United States 31 8.9k 1.0× 5.0k 0.9× 844 0.7× 469 0.8× 637 1.7× 49 10.6k
Kun Qu China 41 7.4k 0.8× 4.0k 0.7× 764 0.6× 224 0.4× 1.2k 3.1× 103 9.5k
Alistair R. R. Forrest Australia 45 6.0k 0.7× 2.3k 0.4× 620 0.5× 370 0.6× 1.2k 3.1× 125 7.8k
Markus Hafner United States 55 10.9k 1.2× 5.2k 0.9× 781 0.6× 365 0.6× 812 2.1× 112 12.5k
Hani Goodarzi United States 36 6.2k 0.7× 3.0k 0.5× 695 0.5× 246 0.4× 592 1.5× 98 7.6k
Sean Lawler United States 46 6.7k 0.8× 3.9k 0.7× 1.9k 1.5× 711 1.2× 1.1k 2.9× 145 10.0k
Michele A. Cleary United States 38 7.5k 0.9× 4.5k 0.8× 1.0k 0.8× 244 0.4× 600 1.6× 62 9.2k
Julja Burchard United States 26 6.3k 0.7× 3.0k 0.5× 527 0.4× 201 0.3× 622 1.6× 47 7.5k
Marc Vooijs Netherlands 45 4.9k 0.6× 1.4k 0.3× 2.0k 1.6× 590 1.0× 633 1.6× 108 8.0k

Countries citing papers authored by Alexander Loewer

Since Specialization
Citations

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

Fields of papers citing papers by Alexander Loewer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alexander Loewer

This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Loewer. A scholar is included among the top collaborators of Alexander Loewer 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 Alexander Loewer. Alexander Loewer 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.
Koeppl, Heinz, et al.. (2025). Decoding stimulus-specific regulation of promoter activity of p53 target genes. Frontiers in Cell and Developmental Biology. 13. 1603603–1603603.
2.
Chen, Jia‐Xuan, Georg Nagel, Petra Beli, et al.. (2024). The p21CIP1-CDK4-DREAM axis is a master regulator of genotoxic stress-induced cellular senescence. Nucleic Acids Research. 52(12). 6945–6963. 11 indexed citations
3.
Becker, Kolja, et al.. (2024). Transcriptional regulators ensuring specific gene expression and decision-making at high TGFβ doses. Life Science Alliance. 8(1). e202402859–e202402859. 3 indexed citations
4.
Bohn, Stefan, et al.. (2023). State- and stimulus-specific dynamics of SMAD signaling determine fate decisions in individual cells. Proceedings of the National Academy of Sciences. 120(10). e2210891120–e2210891120. 6 indexed citations
5.
Loewer, Alexander, et al.. (2023). Resolving Crosstalk Between Signaling Pathways Using Mathematical Modeling and Time-Resolved Single Cell Data. Methods in molecular biology. 2634. 267–284. 1 indexed citations
6.
Loewer, Alexander, et al.. (2022). Data-based stochastic modeling reveals sources of activity bursts in single-cell TGF-β signaling. PLoS Computational Biology. 18(6). e1010266–e1010266. 4 indexed citations
7.
Sheng, Caibin, et al.. (2020). p53 dynamics in single cells are temperature-sensitive. Scientific Reports. 10(1). 1481–1481. 15 indexed citations
8.
Benary, Manuela, et al.. (2020). Disentangling Pro-mitotic Signaling during Cell Cycle Progression using Time-Resolved Single-Cell Imaging. Cell Reports. 31(2). 107514–107514. 13 indexed citations
9.
Herrmann, Andreas, et al.. (2019). Stochastic transcription in the p53‐mediated response to DNA damage is modulated by burst frequency. Molecular Systems Biology. 15(12). e9068–e9068. 27 indexed citations
10.
Sarma, Uddipan, Stefan Bohn, Caibin Sheng, et al.. (2018). Cell‐specific responses to the cytokine TGF β are determined by variability in protein levels. Molecular Systems Biology. 14(1). e7733–e7733. 43 indexed citations
11.
Batchelor, Eric & Alexander Loewer. (2017). Recent progress and open challenges in modeling p53 dynamics in single cells. Current Opinion in Systems Biology. 3. 54–59. 21 indexed citations
12.
Loewer, Alexander, et al.. (2016). Hyperactivation of ATM upon DNA-PKcs inhibition modulates p53 dynamics and cell fate in response to DNA damage. Molecular Biology of the Cell. 27(15). 2360–2367. 53 indexed citations
13.
Rother, Marion, Markus C. Kerr, Munir A. Al‐Zeer, et al.. (2014). Chlamydia infection depends on a functional MDM2-p53 axis. Nature Communications. 5(1). 5201–5201. 69 indexed citations
14.
Memczak, Sebastian, Marvin Jens, Francesca Torti, et al.. (2013). Circular RNAs are a large class of animal RNAs with regulatory potency. Nature. 495(7441). 333–338. 6168 indexed citations breakdown →
15.
Loewer, Alexander, et al.. (2013). The p53 response in single cells is linearly correlated to the number of DNA breaks without a distinct threshold. BMC Biology. 11(1). 114–114. 64 indexed citations
16.
Purvis, Jeremy E., Kyle W. Karhohs, Charles Mock, et al.. (2012). p53 Dynamics Control Cell Fate. Science. 336(6087). 1440–1444. 592 indexed citations breakdown →
17.
Loewer, Alexander & Galit Lahav. (2011). We are all individuals: causes and consequences of non-genetic heterogeneity in mammalian cells. Current Opinion in Genetics & Development. 21(6). 753–758. 59 indexed citations
18.
Batchelor, Eric, Caroline S. Mock, Irun Bhan, Alexander Loewer, & Galit Lahav. (2008). Recurrent Initiation: A Mechanism for Triggering p53 Pulses in Response to DNA Damage. Molecular Cell. 30(3). 277–289. 353 indexed citations
19.
Loewer, Alexander & Galit Lahav. (2006). Cellular Conference Call: External Feedback Affects Cell-Fate Decisions. Cell. 124(6). 1128–1130. 10 indexed citations
20.
Merdes, Gunter, et al.. (2004). Interference of human and Drosophila APP and APP‐like proteins with PNS development in Drosophila. The EMBO Journal. 23(20). 4082–4095. 64 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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