Martin Peifer

33.8k total citations
54 papers, 2.2k citations indexed

About

Martin Peifer is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Martin Peifer has authored 54 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 19 papers in Oncology and 15 papers in Cancer Research. Recurrent topics in Martin Peifer's work include Lung Cancer Research Studies (12 papers), Cancer Genomics and Diagnostics (11 papers) and Lung Cancer Treatments and Mutations (11 papers). Martin Peifer is often cited by papers focused on Lung Cancer Research Studies (12 papers), Cancer Genomics and Diagnostics (11 papers) and Lung Cancer Treatments and Mutations (11 papers). Martin Peifer collaborates with scholars based in Germany, United States and Austria. Martin Peifer's co-authors include Jens Timmer, Roman K. Thomas, Mirjam Koker, William Pao, Martin L. Sos, Johannes M. Heuckmann, Lukas C. Heukamp, Daniel Rauh, Matthias Winterhalder and Björn Schelter and has published in prestigious journals such as Nature, Physical Review Letters and Nucleic Acids Research.

In The Last Decade

Martin Peifer

53 papers receiving 2.1k citations

Peers

Martin Peifer
Laura M. Heiser United States
Tisham De United Kingdom
Hongyoon Choi South Korea
Patrick Danaher United States
Matan Hofree United States
Lucy Yates United Kingdom
Zheng Guo China
Xing Liu China
Laura M. Heiser United States
Martin Peifer
Citations per year, relative to Martin Peifer Martin Peifer (= 1×) peers Laura M. Heiser

Countries citing papers authored by Martin Peifer

Since Specialization
Citations

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

Fields of papers citing papers by Martin Peifer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Peifer

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Peifer. A scholar is included among the top collaborators of Martin Peifer 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 Martin Peifer. Martin Peifer 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.
Kaiser, Laura, Giulia Barbiera, Roman K. Thomas, et al.. (2025). DynaTag for efficient mapping of transcription factors in low-input samples and at single-cell resolution. Nature Communications. 16(1). 6585–6585. 1 indexed citations
2.
Locci, Federica, Martin Peifer, Antonella Montinaro, et al.. (2025). STING induces ZBP1-mediated necroptosis independently of TNFR1 and FADD. Nature. 647(8090). 735–746. 4 indexed citations
3.
Lorenz, Carina, Maria Cartolano, Dennis Plenker, et al.. (2023). Characterizing Evolutionary Dynamics Reveals Strategies to Exhaust the Spectrum of Subclonal Resistance in EGFR-Mutant Lung Cancer. Cancer Research. 83(15). 2471–2479. 7 indexed citations
4.
Klein, Sebastian, Alexander Quaas, Ka‐Won Noh, et al.. (2020). Integrative Analysis of Pleomorphic Dermal Sarcomas Reveals Fibroblastic Differentiation and Susceptibility to Immunotherapy. Clinical Cancer Research. 26(21). 5638–5645. 21 indexed citations
5.
Klein, Sebastian, Alexander Quaas, Jennifer Quantius, et al.. (2020). Deep Learning Predicts HPV Association in Oropharyngeal Squamous Cell Carcinomas and Identifies Patients with a Favorable Prognosis Using Regular H&E Stains. Clinical Cancer Research. 27(4). 1131–1138. 38 indexed citations
6.
Maas, Lukas, Scott Thiebes, Ulrich Lang, et al.. (2019). iRODS metadata management for a cancer genome analysis workflow. BMC Bioinformatics. 20(1). 29–29. 4 indexed citations
7.
Balke‐Want, Hyatt, Philipp Gödel, Nima Abedpour, Martin Peifer, & Peter Borchmann. (2018). Clonal Evolution of a Mutation in PTPRA As a Potential Cause for Resistance Against Anti-CD19 Directed Chimeric Antigen Receptor T-Cell (CAR-T) Therapy with CTL019 in DLBCL Patients. Blood. 132(Supplement 1). 4119–4119. 2 indexed citations
8.
Schmitt, Anna, Gero Knittel, Tsun-Po Yang, et al.. (2017). ATM Deficiency Is Associated with Sensitivity to PARP1- and ATR Inhibitors in Lung Adenocarcinoma. Cancer Research. 77(11). 3040–3056. 82 indexed citations
9.
Malchers, Florian, Meryem S. Ercanoglu, Roberta Castiglione, et al.. (2017). Mechanisms of Primary Drug Resistance in FGFR1 -Amplified Lung Cancer. Clinical Cancer Research. 23(18). 5527–5536. 41 indexed citations
10.
George, Julie, Motonobu Saito, Koji Tsuta, et al.. (2016). Genomic Amplification of CD274 (PD-L1) in Small-Cell Lung Cancer. Clinical Cancer Research. 23(5). 1220–1226. 93 indexed citations
11.
Bouças, Jorge, Christian Fritz, Anna Schmitt, et al.. (2015). Label-Free Protein-RNA Interactome Analysis Identifies Khsrp Signaling Downstream of the p38/Mk2 Kinase Complex as a Critical Modulator of Cell Cycle Progression. PLoS ONE. 10(5). e0125745–e0125745. 29 indexed citations
12.
Chatterjee, Sampurna, Lukas C. Heukamp, Jakob Schöttle, et al.. (2013). Tumor VEGF:VEGFR2 autocrine feed-forward loop triggers angiogenesis in lung cancer. Journal of Clinical Investigation. 123(4). 1732–1740. 164 indexed citations
13.
Heuckmann, Johannes M., Hyatt Balke‐Want, Florian Malchers, et al.. (2012). Differential Protein Stability and ALK Inhibitor Sensitivity of EML4-ALK Fusion Variants. Clinical Cancer Research. 18(17). 4682–4690. 201 indexed citations
14.
Heuckmann, Johannes M., Michael Hölzel, Martin L. Sos, et al.. (2011). ALK Mutations Conferring Differential Resistance to Structurally Diverse ALK Inhibitors. Clinical Cancer Research. 17(23). 7394–7401. 147 indexed citations
15.
Sos, Martin L., Haridas B. Rode, Stefanie Heynck, et al.. (2010). Chemogenomic Profiling Provides Insights into the Limited Activity of Irreversible EGFR Inhibitors in Tumor Cells Expressing the T790M EGFR Resistance Mutation. Cancer Research. 70(3). 868–874. 175 indexed citations
16.
Peifer, Martin, Jonathan M. Weiss, Martin L. Sos, et al.. (2010). Analysis of Compound Synergy in High-Throughput Cellular Screens by Population-Based Lifetime Modeling. PLoS ONE. 5(1). e8919–e8919. 22 indexed citations
17.
Chmielecki, Juliann, Martin Peifer, Peilin Jia, et al.. (2010). Targeted next-generation sequencing of DNA regions proximal to a conserved GXGXXG signaling motif enables systematic discovery of tyrosine kinase fusions in cancer. Nucleic Acids Research. 38(20). 6985–6996. 35 indexed citations
18.
Gong, Yixuan, Evelyn Yao, Ronglai Shen, et al.. (2009). High Expression Levels of Total IGF-1R and Sensitivity of NSCLC Cells In Vitro to an Anti-IGF-1R Antibody (R1507). PLoS ONE. 4(10). e7273–e7273. 112 indexed citations
19.
Mugal, Carina F., H. H. von Grünberg, & Martin Peifer. (2008). Transcription-Induced Mutational Strand Bias and Its Effect on Substitution Rates in Human Genes. Molecular Biology and Evolution. 26(1). 131–142. 51 indexed citations
20.
Karro, John, Martin Peifer, Ross C. Hardison, Martina Kollmann, & H. H. von Grünberg. (2007). Exponential Decay of GC Content Detected by Strand-Symmetric Substitution Rates Influences the Evolution of Isochore Structure. Molecular Biology and Evolution. 25(2). 362–374. 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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