Ted R. Hupp

29.4k total citations · 1 hit paper
234 papers, 8.6k citations indexed

About

Ted R. Hupp is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Ted R. Hupp has authored 234 papers receiving a total of 8.6k indexed citations (citations by other indexed papers that have themselves been cited), including 165 papers in Molecular Biology, 117 papers in Oncology and 38 papers in Cell Biology. Recurrent topics in Ted R. Hupp's work include Cancer-related Molecular Pathways (98 papers), Ubiquitin and proteasome pathways (44 papers) and Cancer Research and Treatments (37 papers). Ted R. Hupp is often cited by papers focused on Cancer-related Molecular Pathways (98 papers), Ubiquitin and proteasome pathways (44 papers) and Cancer Research and Treatments (37 papers). Ted R. Hupp collaborates with scholars based in United Kingdom, Czechia and Poland. Ted R. Hupp's co-authors include David P. Lane, David W. Meek, Carol Midgley, Bořivoj Vojtěšek, Kathryn L. Ball, Alison Sparks, Ashley Craig, Lindsay Burch, Nicola J. MacLaine and Jeremy P. Blaydes and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Ted R. Hupp

223 papers receiving 8.4k citations

Hit Papers

Regulation of the specific DNA binding function of p53 1992 2026 2003 2014 1992 250 500 750

Peers

Ted R. Hupp
John C. Reed United States
Nicholas B. La Thangue United Kingdom
Onno Kranenburg Netherlands
Martha R. Stampfer United States
Maureen E. Murphy United States
Kristoffer Valerie United States
Ted R. Hupp
Citations per year, relative to Ted R. Hupp Ted R. Hupp (= 1×) peers Bořivoj Vojtěšek

Countries citing papers authored by Ted R. Hupp

Since Specialization
Citations

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

Fields of papers citing papers by Ted R. Hupp

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ted R. Hupp. 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 Ted R. Hupp. The network helps show where Ted R. Hupp may publish in the future.

Co-authorship network of co-authors of Ted R. Hupp

This figure shows the co-authorship network connecting the top 25 collaborators of Ted R. Hupp. A scholar is included among the top collaborators of Ted R. Hupp 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 Ted R. Hupp. Ted R. Hupp 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.
Ren, Bo, Darryl B. Hardie, Mariya I. Goncheva, et al.. (2025). Proteomic Changes in Cancer Cell Lines as a Result of Bacterial Infection. PROTEOMICS. e70062–e70062.
2.
Goodlett, David R., et al.. (2024). Mass Spectrometry Advances in Analysis of Glioblastoma. Mass Spectrometry Reviews. 44(4). 630–664. 1 indexed citations
3.
Hupp, Ted R., et al.. (2024). Inverse correlation between TP53 gene status and PD-L1 protein levels in a melanoma cell model depends on an IRF1/SOX10 regulatory axis. Cellular & Molecular Biology Letters. 29(1). 117–117. 3 indexed citations
4.
Dziubek, Katarzyna, Katarzyna Węgrzyn, Bořivoj Vojtěšek, et al.. (2024). Comparative characterization of two monoclonal antibodies targeting canine PD-1. Frontiers in Immunology. 15. 1382576–1382576.
5.
Boyle, Shelagh, et al.. (2023). FISH analysis reveals CDKN2A and IFNA14 co-deletion is heterogeneous and is a prominent feature of glioblastoma. Brain Tumor Pathology. 41(1). 4–17. 4 indexed citations
6.
Kaźmierczak-Siedlecka, Karolina, Karolina Skonieczna‐Żydecka, Ted R. Hupp, et al.. (2022). Next-generation probiotics – do they open new therapeutic strategies for cancer patients?. Gut Microbes. 14(1). 2035659–2035659. 86 indexed citations
7.
Piekarska, Karolina, Zuzanna Urban‐Wójciuk, Małgorzata Kurkowiak, et al.. (2022). Mesenchymal stem cells transfer mitochondria to allogeneic Tregs in an HLA-dependent manner improving their immunosuppressive activity. Nature Communications. 13(1). 856–856. 57 indexed citations
8.
Faktor, Jakub, Marta Nekulová, Lenka Hernychová, et al.. (2022). Emergent Role of IFITM1/3 towards Splicing Factor (SRSF1) and Antigen-Presenting Molecule (HLA-B) in Cervical Cancer. Biomolecules. 12(8). 1090–1090. 1 indexed citations
9.
Minoli, Lucia, Selina Iussich, Emanuela Morello, et al.. (2022). Development of Monoclonal Antibodies Targeting Canine PD-L1 and PD-1 and Their Clinical Relevance in Canine Apocrine Gland Anal Sac Adenocarcinoma. Cancers. 14(24). 6188–6188. 9 indexed citations
10.
Kalathiya, Umesh, Monikaben Padariya, Robin Fåhræus, Soumyananda Chakraborti, & Ted R. Hupp. (2021). Multivalent Display of SARS-CoV-2 Spike (RBD Domain) of COVID-19 to Nanomaterial, Protein Ferritin Nanocages. Biomolecules. 11(2). 297–297. 23 indexed citations
11.
Kurkowiak, Małgorzata, Zuzanna Urban‐Wójciuk, Liam P. Keegan, et al.. (2021). The effects of RNA editing in cancer tissue at different stages in carcinogenesis. RNA Biology. 18(11). 1524–1539. 18 indexed citations
12.
Kurkowiak, Małgorzata, Jakub Faktor, J. Robert O’Neill, et al.. (2021). An integrated DNA and RNA variant detector identifies a highly conserved three base exon in the MAP4K5 kinase locus. RNA Biology. 18(12). 2556–2575. 1 indexed citations
13.
Piróg, Artur, Jakub Faktor, Zuzanna Urban‐Wójciuk, et al.. (2021). Comparison of different digestion methods for proteomic analysis of isolated cells and FFPE tissue samples. Talanta. 233. 122568–122568. 16 indexed citations
14.
Curran, Olimpia E., Javier A. Alfaro, Jacek Kowalski, et al.. (2021). Kinomics platform using GBM tissue identifies BTK as being associated with higher patient survival. Life Science Alliance. 4(12). e202101054–e202101054. 8 indexed citations
15.
Kunath, Tilo, et al.. (2017). Mono‐Substituted Hydrocarbon Diastereomer Combinations Reveal Stapled Peptides with High Structural Fidelity. Chemistry - A European Journal. 24(9). 2094–2097. 5 indexed citations
16.
Murray, Euan, et al.. (2014). Engineering a synthetic cell panel to identify signalling components reprogrammed by the cell growth regulator anterior gradient-2. Molecular BioSystems. 10(6). 1409–1425. 15 indexed citations
17.
Morgan, Hugh P., Francis J. O’Reilly, Martin A. Wear, et al.. (2013). M2 pyruvate kinase provides a mechanism for nutrient sensing and regulation of cell proliferation. Proceedings of the National Academy of Sciences. 110(15). 5881–5886. 143 indexed citations
18.
Marcar, Lynnette, Nicola J. MacLaine, Ted R. Hupp, & David W. Meek. (2010). Mage-A Cancer/Testis Antigens Inhibit p53 Function by Blocking Its Interaction with Chromatin. Cancer Research. 70(24). 10362–10370. 127 indexed citations
19.
Dornan, David, et al.. (2004). Interferon Regulatory Factor 1 Binding to p300 Stimulates DNA-Dependent Acetylation of p53. Molecular and Cellular Biology. 24(22). 10083–10098. 65 indexed citations
20.
Pöhler, Elizabeth, et al.. (2003). Gene Transfer for the Esophagus— an Ex Vivo Study Demonstrating Transfected Gene Expression in the Human Esophagus. Discovery Research Portal (University of Dundee). 3(4). 441–448. 1 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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