Hubert Stöppler

2.3k total citations
31 papers, 1.3k citations indexed

About

Hubert Stöppler is a scholar working on Molecular Biology, Oncology and Epidemiology. According to data from OpenAlex, Hubert Stöppler has authored 31 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 11 papers in Oncology and 11 papers in Epidemiology. Recurrent topics in Hubert Stöppler's work include Cervical Cancer and HPV Research (9 papers), Cancer-related Molecular Pathways (7 papers) and Virus-based gene therapy research (5 papers). Hubert Stöppler is often cited by papers focused on Cervical Cancer and HPV Research (9 papers), Cancer-related Molecular Pathways (7 papers) and Virus-based gene therapy research (5 papers). Hubert Stöppler collaborates with scholars based in United States, Germany and China. Hubert Stöppler's co-authors include Richard Schlegel, Melissa C. Stoppler, Peter R. Carroll, Robert Blelloch, Joan F. Hilton, Lauren Baehner, Lawrence Fong, Felix Moltzahn, Andrew S. Peek and Jeffry Simko and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and PLoS ONE.

In The Last Decade

Hubert Stöppler

31 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hubert Stöppler United States 18 701 344 325 254 136 31 1.3k
Kevin Hakala United States 20 809 1.2× 118 0.3× 147 0.5× 207 0.8× 149 1.1× 31 1.2k
Tsutomu Tanaka Japan 19 428 0.6× 227 0.7× 120 0.4× 123 0.5× 119 0.9× 36 996
Ji‐Liang Li China 17 914 1.3× 204 0.6× 609 1.9× 291 1.1× 108 0.8× 41 1.6k
Hsuan Liu Taiwan 22 1.1k 1.6× 211 0.6× 444 1.4× 269 1.1× 65 0.5× 69 1.9k
Kefeng Lu China 22 1.3k 1.8× 573 1.7× 205 0.6× 321 1.3× 94 0.7× 55 2.0k
Sunjoo Jeong South Korea 26 1.4k 2.1× 186 0.5× 352 1.1× 234 0.9× 69 0.5× 68 1.9k
Kazuharu Shimizu Japan 20 1.3k 1.8× 170 0.5× 968 3.0× 129 0.5× 53 0.4× 30 1.8k
Yannan Qin China 18 653 0.9× 151 0.4× 203 0.6× 77 0.3× 81 0.6× 40 1.0k

Countries citing papers authored by Hubert Stöppler

Since Specialization
Citations

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

Fields of papers citing papers by Hubert Stöppler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hubert Stöppler

This figure shows the co-authorship network connecting the top 25 collaborators of Hubert Stöppler. A scholar is included among the top collaborators of Hubert Stöppler 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 Hubert Stöppler. Hubert Stöppler 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.
Li, Ruidong, Huang Huang, Christine Wan, et al.. (2024). Single-cell sequencing of full-length transcripts and T-cell receptors with automated high-throughput Smart-seq3. BMC Genomics. 25(1). 1127–1127. 4 indexed citations
2.
Draanen, Jenna van, Pamela L. Davidson, H Bour, et al.. (2016). Assessing Researcher Needs for a Virtual Biobank. Biopreservation and Biobanking. 15(3). 203–210. 17 indexed citations
3.
Wang, Siao‐Yi, Stephen Shiboski, Cassandra D. Belair, et al.. (2014). miR-19, miR-345, miR-519c-5p Serum Levels Predict Adverse Pathology in Prostate Cancer Patients Eligible for Active Surveillance. PLoS ONE. 9(6). e98597–e98597. 46 indexed citations
4.
Zhang, Shulin, Yi‐Lin Yang, Yucheng Wang, et al.. (2014). CK2α, over-expressed in human malignant pleural mesothelioma, regulates the Hedgehog signaling pathway in mesothelioma cells. Journal of Experimental & Clinical Cancer Research. 33(1). 93–93. 24 indexed citations
5.
Moltzahn, Felix, Adam B. Olshen, Lauren Baehner, et al.. (2010). Microfluidic-Based Multiplex qRT-PCR Identifies Diagnostic and Prognostic microRNA Signatures in the Sera of Prostate Cancer Patients. Cancer Research. 71(2). 550–560. 274 indexed citations
6.
Arnouk, Hilal, Mark A. Merkley, Robert H. Podolsky, et al.. (2009). Characterization of molecular markers indicative of cervical cancer progression. PROTEOMICS - CLINICAL APPLICATIONS. 3(5). 516–527. 69 indexed citations
7.
Merkley, Mark A., Ellen Hildebrandt, Robert H. Podolsky, et al.. (2009). Large-scale analysis of protein expression changes in human keratinocytes immortalized by human papilloma virus type 16 E6 and E7 oncogenes. Proteome Science. 7(1). 29–29. 23 indexed citations
8.
Hsu, Stephen, Douglas Dickinson, Haiyan Qin, et al.. (2007). Green tea polyphenols reduce autoimmune symptoms in a murine model for human Sjogren's syndrome and protect human salivary acinar cells from TNF-α-induced cytotoxicity. Autoimmunity. 40(2). 138–147. 45 indexed citations
9.
Stöppler, Hubert, Sachiyo Nomura, H. Yamaguchi, et al.. (2005). Saturation labeling with cysteine‐reactive cyanine fluorescent dyes provides increased sensitivity for protein expression profiling of laser‐microdissected clinical specimens. PROTEOMICS. 5(7). 1746–1757. 65 indexed citations
10.
Alfke, Heiko, et al.. (2003). In Vitro MR Imaging of Regulated Gene Expression. Radiology. 228(2). 488–492. 48 indexed citations
11.
12.
Malerczyk, Claudius, et al.. (2002). Monitoring daunorubicin-induced alterations in protein expression in pancreas carcinoma cells by two-dimensional gel electrophoresis. PROTEOMICS. 2(6). 697–705. 19 indexed citations
13.
14.
Stöppler, Hubert, Melissa C. Stoppler, Michael Kisiela, et al.. (2001). Telomerase activity of Merkel cell carcinomas and Merkel cell carcinoma-derived cell cultures. Archives of Dermatological Research. 293(8). 397–406. 5 indexed citations
15.
Stöppler, Hubert, Melissa C. Stoppler, Elizabeth Johnson, et al.. (1998). The E7 protein of human papillomavirus type 16 sensitizes primary human keratinocytes to apoptosis. Oncogene. 17(10). 1207–1214. 93 indexed citations
16.
Stöppler, Hubert, Dan-Paul Hartmann, Levana Sherman, & Richard Schlegel. (1997). The Human Papillomavirus Type 16 E6 and E7 Oncoproteins Dissociate Cellular Telomerase Activity from the Maintenance of Telomere Length. Journal of Biological Chemistry. 272(20). 13332–13337. 103 indexed citations
17.
Araujo, John C., Jay Doniger, Hubert Stöppler, M. Reza Sadaie, & Leonard J. Rosenthal. (1997). Cell lines containing and expressing the human herpesvirus 6A ts gene are protected from both H-ras and BPV-1 transformation. Oncogene. 14(8). 937–943. 11 indexed citations
18.
Stöppler, Hubert, et al.. (1996). Influence of human papillomavirus type 16 gene expression on in vitro differentiation of the human teratocarcinoma cell line 2102Ep. Molecular Carcinogenesis. 16(2). 109–114. 1 indexed citations
19.
Stoppler, Melissa C., Keith A. Ching, Hubert Stöppler, et al.. (1996). Natural variants of the human papillomavirus type 16 E6 protein differ in their abilities to alter keratinocyte differentiation and to induce p53 degradation. Journal of Virology. 70(10). 6987–6993. 129 indexed citations
20.
Stöppler, Hubert, Melissa C. Stoppler, & Richard Schlegel. (1994). Transforming Proteins of the Papillomaviruses. Intervirology. 37(3-4). 168–179. 20 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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