Martin Scherzer

943 total citations
10 papers, 636 citations indexed

About

Martin Scherzer is a scholar working on Oncology, Molecular Biology and Modeling and Simulation. According to data from OpenAlex, Martin Scherzer has authored 10 papers receiving a total of 636 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Oncology, 4 papers in Molecular Biology and 3 papers in Modeling and Simulation. Recurrent topics in Martin Scherzer's work include Cancer Cells and Metastasis (6 papers), Mathematical Biology Tumor Growth (3 papers) and 3D Printing in Biomedical Research (3 papers). Martin Scherzer is often cited by papers focused on Cancer Cells and Metastasis (6 papers), Mathematical Biology Tumor Growth (3 papers) and 3D Printing in Biomedical Research (3 papers). Martin Scherzer collaborates with scholars based in Austria, Sweden and Germany. Martin Scherzer's co-authors include Christine Unger, Markus Hengstschläger, Helmut Dolznig, Nina Kramer, Angelika Walzl, Daniela Unterleuthner, Albin Rudisch, Wolfgang Sommergruber, Stefanie Walter and Mira Stadler and has published in prestigious journals such as Advanced Drug Delivery Reviews, Oncogene and Scientific Reports.

In The Last Decade

Martin Scherzer

10 papers receiving 629 citations

Peers

Martin Scherzer

MB

ONCOL

BE

CR

CB

Matthias Gutekunst Germany

Marc Osterland Germany

Alvin Lo United States

Brittany L. Allen-Petersen United States

Karoline Pudelko Austria

Dan G. Duda United States

Jinxiang Tan China

Ori Maller United States

Yashira L. Negrón Abril United States

Amir Barzegar Behrooz Iran

Matthias Gutekunst Germany

Martin Scherzer

276 ×0.9

MB

309 ×1.0

ONCOL

216 ×1.2

BE

98 ×0.8

CR

70 ×1.0

CB

Citations per year, relative to Martin Scherzer Martin Scherzer (= 1×) peers Matthias Gutekunst

Countries citing papers authored by Martin Scherzer

Since Specialization

Citations

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

Fields of papers citing papers by Martin Scherzer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Scherzer

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

All Works

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10 of 10 papers shown

1.

Scherzer, Martin, et al.. (2022). Recruitment of Scc2/4 to double-strand breaks depends on γH2A and DNA end resection. Life Science Alliance. 5(5). e202101244–e202101244. 11 indexed citations

2.

Hosaka, Kayoko, Yunlong Yang, Masaki Nakamura, et al.. (2018). Dual roles of endothelial FGF-2–FGFR1–PDGF-BB and perivascular FGF-2–FGFR2–PDGFRβ signaling pathways in tumor vascular remodeling. Cell Discovery. 4(1). 3–3. 45 indexed citations

3.

Stadler, Mira, Martin Scherzer, Stefanie Walter, et al.. (2018). Exclusion from spheroid formation identifies loss of essential cell-cell adhesion molecules in colon cancer cells. Scientific Reports. 8(1). 1151–1151. 67 indexed citations

4.

Kramer, Nina, Christine Unger, Harini Nivarthi, et al.. (2017). Autocrine WNT2 signaling in fibroblasts promotes colorectal cancer progression. Oncogene. 36(39). 5460–5472. 105 indexed citations

5.

Unger, Christine, Nina Kramer, Daniela Unterleuthner, et al.. (2017). Stromal-derived IGF2 promotes colon cancer progression via paracrine and autocrine mechanisms. Oncogene. 36(38). 5341–5355. 61 indexed citations

6.

Stadler, Mira, Stefanie Walter, Angelika Walzl, et al.. (2015). Increased complexity in carcinomas: Analyzing and modeling the interaction of human cancer cells with their microenvironment. Seminars in Cancer Biology. 35. 107–124. 52 indexed citations

7.

Rupp, Christian, Martin Scherzer, Albin Rudisch, et al.. (2014). IGFBP7, a novel tumor stroma marker, with growth-promoting effects in colon cancer through a paracrine tumor–stroma interaction. Oncogene. 34(7). 815–825. 96 indexed citations

8.

Unger, Christine, Nina Kramer, Angelika Walzl, et al.. (2014). Modeling human carcinomas: Physiologically relevant 3D models to improve anti-cancer drug development. Advanced Drug Delivery Reviews. 79-80. 50–67. 116 indexed citations

9.

Walzl, Angelika, Christine Unger, Nina Kramer, et al.. (2014). The Resazurin Reduction Assay Can Distinguish Cytotoxic from Cytostatic Compounds in Spheroid Screening Assays. SLAS DISCOVERY. 19(7). 1047–1059. 74 indexed citations

10.

Fujii, Yuji, et al.. (2006). Dynamic Characterization of Wet Friction Component under Realistic Transmission Shift Conditions. SAE technical papers on CD-ROM/SAE technical paper series. 1. 9 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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