Robert Eferl

9.4k total citations · 1 hit paper
68 papers, 6.7k citations indexed

About

Robert Eferl is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Robert Eferl has authored 68 papers receiving a total of 6.7k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Molecular Biology, 30 papers in Oncology and 16 papers in Immunology. Recurrent topics in Robert Eferl's work include Cytokine Signaling Pathways and Interactions (13 papers), Liver physiology and pathology (9 papers) and Bone Metabolism and Diseases (9 papers). Robert Eferl is often cited by papers focused on Cytokine Signaling Pathways and Interactions (13 papers), Liver physiology and pathology (9 papers) and Bone Metabolism and Diseases (9 papers). Robert Eferl collaborates with scholars based in Austria, Germany and Spain. Robert Eferl's co-authors include Erwin F. Wagner, Lukas Kenner, Rainer Zenz, Martina Rath, Harald Scheuch, Roméo Ricci, Erwin Tschachler, Astrid Hoebertz, Peter Angel and Jean‐Pierre David and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Robert Eferl

68 papers receiving 6.6k citations

Hit Papers

AP-1: a double-edged sword in tumorigenesis 2003 2026 2010 2018 2003 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robert Eferl Austria 33 3.8k 2.0k 1.4k 1.3k 613 68 6.7k
Kazuhito Naka Japan 40 4.0k 1.1× 2.0k 1.0× 1.0k 0.7× 1.6k 1.3× 335 0.5× 92 7.3k
Yoichi Furukawa Japan 48 6.5k 1.7× 2.3k 1.2× 1.1k 0.8× 1.6k 1.3× 794 1.3× 183 9.6k
Kazuyoshi Yanagihara Japan 49 5.0k 1.3× 2.2k 1.1× 864 0.6× 1.7k 1.4× 1.1k 1.8× 215 7.8k
Gloria H. Su United States 43 2.8k 0.7× 2.4k 1.2× 905 0.7× 1.3k 1.0× 484 0.8× 91 5.8k
Jochen Heß Germany 36 3.2k 0.9× 1.4k 0.7× 1.4k 1.0× 1.2k 1.0× 601 1.0× 125 5.8k
Luisa Lanfrancone Italy 38 4.9k 1.3× 1.6k 0.8× 1.2k 0.9× 813 0.6× 379 0.6× 95 7.8k
David Danielpour United States 55 5.8k 1.5× 1.8k 0.9× 1.3k 0.9× 1.3k 1.0× 1.1k 1.8× 135 9.5k
Alfred S.L. Cheng Hong Kong 51 5.4k 1.4× 1.4k 0.7× 867 0.6× 2.5k 2.0× 747 1.2× 146 8.2k
Lopa Mishra United States 49 3.8k 1.0× 2.7k 1.4× 634 0.5× 1.5k 1.2× 819 1.3× 169 7.8k
Xia Lin China 44 4.7k 1.2× 1.2k 0.6× 650 0.5× 991 0.8× 419 0.7× 124 6.2k

Countries citing papers authored by Robert Eferl

Since Specialization
Citations

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

Fields of papers citing papers by Robert Eferl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robert Eferl

This figure shows the co-authorship network connecting the top 25 collaborators of Robert Eferl. A scholar is included among the top collaborators of Robert Eferl 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 Robert Eferl. Robert Eferl 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.
John, Daniel, J. Thomas Hannich, Clemens Fürnsinn, et al.. (2025). Loss of SPHK1 fuels inflammation to drive KRAS-mutated lung adenocarcinoma. Cancer Letters. 623. 217733–217733. 1 indexed citations
2.
Moser, Doris, Katy Schmidt, Petra Pjevac, et al.. (2023). Defects in microvillus crosslinking sensitize to colitis and inflammatory bowel disease. EMBO Reports. 24(10). e57084–e57084. 11 indexed citations
3.
Schepelmann, Martin, Ildikó Mesteri, Teresa Manhardt, et al.. (2022). AOM/DSS Induced Colitis-Associated Colorectal Cancer in 14-Month-Old Female Balb/C and C57/Bl6 Mice—A Pilot Study. International Journal of Molecular Sciences. 23(9). 5278–5278. 19 indexed citations
4.
Rohr‐Udilova, Nataliya, Kaoru Tsuchiya, Gerald Timelthaler, et al.. (2021). Morphometric Analysis of Mast Cells in Tumor Predicts Recurrence of Hepatocellular Carcinoma After Liver Transplantation. Hepatology Communications. 5(11). 1939–1952. 9 indexed citations
5.
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
6.
Schütz, Birgit, Gerald Timelthaler, Robert Eferl, et al.. (2016). Generation of metastatic melanoma specific antibodies by affinity purification. Scientific Reports. 6(1). 37253–37253. 2 indexed citations
7.
Stein, Ilan, Yair Klieger, Rinnat M. Porat, et al.. (2014). Acquisition of an immunosuppressive protumorigenic macrophage phenotype depending on c-Jun phosphorylation. Proceedings of the National Academy of Sciences. 111(49). 17582–17587. 47 indexed citations
8.
Evstatiev, Rayko, Adam Bukaty, Kristine Jimenez, et al.. (2014). Iron deficiency alters megakaryopoiesis and platelet phenotype independent of thrombopoietin. American Journal of Hematology. 89(5). 524–529. 80 indexed citations
9.
Lassnig, Caroline, Susanne Heider, Zsuzsanna Bagó-Horváth, et al.. (2014). Inducible, Dose-Adjustable and Time-Restricted Reconstitution of Stat1 Deficiency In Vivo. PLoS ONE. 9(1). e86608–e86608. 10 indexed citations
10.
Eferl, Robert. (2013). CCL2 at the crossroad of cancer metastasis. PubMed. 2(2). e23816–e23816. 9 indexed citations
11.
Rohr‐Udilova, Nataliya, Wolfgang Sieghart, Robert Eferl, et al.. (2011). Antagonistic effects of selenium and lipid peroxides on growth control in early hepatocellular carcinoma. Hepatology. 55(4). 1112–1121. 59 indexed citations
12.
Casanova, Emilio, et al.. (2011). Genetically modified mouse models of cancer invasion and metastasis. Drug Discovery Today Disease Models. 8(2-3). 67–74. 21 indexed citations
13.
Eferl, Robert, Rainer Zenz, Hans‐Christian Theussl, & Erwin F. Wagner. (2007). Simultaneous generation of fra‐2 conditional and fra‐2 knock‐out mice. genesis. 45(7). 447–451. 25 indexed citations
14.
Bakiri, Latifa, Yasunari Takada, Martin Radolf, et al.. (2007). Role of heterodimerization of c-Fos and Fra1 proteins in osteoclast differentiation. Bone. 40(4). 867–875. 27 indexed citations
15.
Ricci, Roméo, Urs Eriksson, Gavin Y. Oudit, et al.. (2005). Distinct functions of junD in cardiac hypertrophy and heart failure. Genes & Development. 19(2). 208–213. 39 indexed citations
16.
Karreth, Florian A., Astrid Hoebertz, Harald Scheuch, Robert Eferl, & Erwin F. Wagner. (2004). The AP1 transcription factor Fra2 is required for efficient cartilage development. Development. 131(22). 5717–5725. 74 indexed citations
17.
Eferl, Robert, Astrid Hoebertz, Arndt F. Schilling, et al.. (2004). The Fos‐related antigen Fra‐1 is an activator of bone matrix formation. The EMBO Journal. 23(14). 2789–2799. 159 indexed citations
18.
Hoebertz, Astrid, et al.. (2003). Loss of Fra-2 expression leads to osteoporosis. Calcified Tissue International. 72(4). 329. 1 indexed citations
19.
Fleischmann, Alexander, et al.. (2003). Rhabdomyosarcoma development in mice lacking Trp53 and Fos. Cancer Cell. 4(6). 477–482. 56 indexed citations
20.
Nöhammer, Christa, Yosuf El‐Shabrawi, Silvia Schauer, et al.. (2000). cDNA cloning and analysis of tissue‐specific expression of mouse peroxisomal straight‐chain acyl‐CoA oxidase. European Journal of Biochemistry. 267(4). 1254–1260. 32 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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