Joerg Heyer

4.4k total citations · 1 hit paper
24 papers, 2.7k citations indexed

About

Joerg Heyer is a scholar working on Molecular Biology, Cancer Research and Pathology and Forensic Medicine. According to data from OpenAlex, Joerg Heyer has authored 24 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 11 papers in Cancer Research and 10 papers in Pathology and Forensic Medicine. Recurrent topics in Joerg Heyer's work include Genetic factors in colorectal cancer (9 papers), Cancer Genomics and Diagnostics (8 papers) and TGF-β signaling in diseases (5 papers). Joerg Heyer is often cited by papers focused on Genetic factors in colorectal cancer (9 papers), Cancer Genomics and Diagnostics (8 papers) and TGF-β signaling in diseases (5 papers). Joerg Heyer collaborates with scholars based in United States. Joerg Heyer's co-authors include Martin Lipkin, Kan Yang, Raju Kucherlapati, Raju Kucherlapati, Marie Lia, Wancai Yang, Leonard H. Augenlicht, Anna Velcich, Courtney Nicholas and Alessandra Fragale and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Joerg Heyer

24 papers receiving 2.6k citations

Hit Papers

Colorectal Cancer in Mice Genetically Deficient in the Mu... 2002 2026 2010 2018 2002 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joerg Heyer United States 16 1.8k 738 709 497 421 24 2.7k
Béatrice Romagnolo France 20 2.0k 1.1× 851 1.2× 343 0.5× 322 0.6× 667 1.6× 36 3.0k
Ferenc Sípos Hungary 28 1.1k 0.6× 832 1.1× 453 0.6× 583 1.2× 257 0.6× 128 2.3k
Françoise Praz France 28 1.0k 0.6× 1.1k 1.5× 804 1.1× 501 1.0× 197 0.5× 63 2.4k
Hans‐Dieter Royer Germany 29 2.1k 1.2× 932 1.3× 442 0.6× 598 1.2× 308 0.7× 48 3.2k
Jun-ichi Furuyama Japan 26 1.1k 0.6× 426 0.6× 379 0.5× 288 0.6× 379 0.9× 71 2.2k
Orsolya Galamb Hungary 27 1.0k 0.6× 532 0.7× 364 0.5× 660 1.3× 163 0.4× 83 1.7k
Pantelis Hatzis Greece 25 2.3k 1.3× 859 1.2× 196 0.3× 388 0.8× 771 1.8× 41 3.3k
Koen Kas Belgium 21 1.1k 0.6× 613 0.8× 261 0.4× 228 0.5× 358 0.9× 46 2.3k
В. И. Кашуба Sweden 31 2.4k 1.3× 596 0.8× 217 0.3× 786 1.6× 369 0.9× 159 3.1k
Martin S. Staege Germany 23 1.4k 0.8× 669 0.9× 331 0.5× 356 0.7× 158 0.4× 108 2.7k

Countries citing papers authored by Joerg Heyer

Since Specialization
Citations

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

Fields of papers citing papers by Joerg Heyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joerg Heyer

This figure shows the co-authorship network connecting the top 25 collaborators of Joerg Heyer. A scholar is included among the top collaborators of Joerg Heyer 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 Joerg Heyer. Joerg Heyer 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.
Eifert, Cheryl, Angeliki Pantazi, Ruobai Sun, et al.. (2017). Clinical Application of a Cancer Genomic Profiling Assay to Guide Precision Medicine Decisions. Personalized Medicine. 14(4). 309–325. 23 indexed citations
2.
Zhou, Yinghui, William M. Rideout, Sireesha Yalavarthi, et al.. (2014). Spontaneous Genomic Alterations in a Chimeric Model of Colorectal Cancer Enable Metastasis and Guide Effective Combinatorial Therapy. PLoS ONE. 9(8). e105886–e105886. 13 indexed citations
4.
O’Hagan, Rónán C. & Joerg Heyer. (2011). KRAS Mouse Models: Modeling Cancer Harboring KRAS Mutations. Genes & Cancer. 2(3). 335–343. 24 indexed citations
5.
Heyer, Joerg, Lawrence N. Kwong, Scott W. Lowe, & Lynda Chin. (2010). Non-germline genetically engineered mouse models for translational cancer research. Nature reviews. Cancer. 10(7). 470–480. 131 indexed citations
6.
Watters, James, Chun Cheng, Pradip K. Majumder, et al.. (2009). De novo Discovery of a γ-Secretase Inhibitor Response Signature Using a Novel In vivo Breast Tumor Model. Cancer Research. 69(23). 8949–8957. 31 indexed citations
7.
Zhou, Yinghui, William M. Rideout, Tong Zi, et al.. (2009). Chimeric mouse tumor models reveal differences in pathway activation between ERBB family– and KRAS-dependent lung adenocarcinomas. Nature Biotechnology. 28(1). 71–78. 59 indexed citations
8.
Zi, Tong, William M. Rideout, M. Isabel Chiu, et al.. (2009). Abstract A22: Response to the triple VEGFR inhibitor tivozanib (AV-951) in KRAS and EGFR driven lung tumors developed in chimeric mouse models. Molecular Cancer Therapeutics. 8(12_Supplement). A22–A22. 1 indexed citations
9.
Farlow, Samuel J., Tong Zi, Xiao‐Jian Sun, et al.. (2009). Abstract A12: Variation in response to triple VEGFR inhibitor tivozanib in mouse models of hepatocellular carcinoma. Molecular Cancer Therapeutics. 8(12_Supplement). A12–A12. 4 indexed citations
10.
Yang, Yaw-Ching, Ester Piek, Jiří Zavadil, et al.. (2003). Hierarchical model of gene regulation by transforming growth factor β. Proceedings of the National Academy of Sciences. 100(18). 10269–10274. 177 indexed citations
11.
Velcich, Anna, Wancai Yang, Joerg Heyer, et al.. (2002). Colorectal Cancer in Mice Genetically Deficient in the Mucin Muc2. Science. 295(5560). 1726–1729. 753 indexed citations breakdown →
12.
Heyer, Joerg, et al.. (2002). Conditional inactivation of the dopamine receptor 5 gene: Flanking the Drd5 gene with loxP sites. genesis. 32(2). 102–104. 4 indexed citations
13.
Kucherlapati, Melanie H., Kan Yang, Mari Kuraguchi, et al.. (2002). Haploinsufficiency of Flap endonuclease ( Fen1 ) leads to rapid tumor progression. Proceedings of the National Academy of Sciences. 99(15). 9924–9929. 197 indexed citations
14.
Edelmann, Winfried, Asad Umar, Kan Yang, et al.. (2000). The DNA mismatch repair genes Msh3 and Msh6 cooperate in intestinal tumor suppression.. PubMed. 60(4). 803–7. 132 indexed citations
15.
Edelmann, Winfried, Paula E. Cohen, Burkhard Kneitz, et al.. (1999). Mammalian MutS homologue 5 is required for chromosome pairing in meiosis. Nature Genetics. 21(1). 123–127. 312 indexed citations
16.
Heyer, Joerg, Kan Yang, Martin Lipkin, Winfried Edelmann, & Raju Kucherlapati. (1999). Mouse models for colorectal cancer. Oncogene. 18(38). 5325–5333. 94 indexed citations
17.
Yang, Yaw-Ching, Ester Piek, Aldo Massimi, et al.. (1999). Genetic/genomic analysis of signal transduction pathways using cDNA microarray technology. Nature Genetics. 23(S3). 34–34. 2 indexed citations
18.
Heyer, Joerg, Diana Escalante‐Alcalde, Marie Lia, et al.. (1999). Postgastrulation Smad2- deficient embryos show defects in embryo turning and anterior morphogenesis. Proceedings of the National Academy of Sciences. 96(22). 12595–12600. 132 indexed citations
19.
Saint-Jore, Bruno, Anne Puech, Joerg Heyer, et al.. (1998). Goosecoid-like (GSCL), a candidate gene for velocardiofacial syndrome, is not essential for normal mouse development. Human Molecular Genetics. 7(12). 1841–1849. 19 indexed citations
20.
Edelmann, Winfried, Kan Yang, Asad Umar, et al.. (1997). Mutation in the Mismatch Repair Gene Msh6 Causes Cancer Susceptibility. Cell. 91(4). 467–477. 304 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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