John F. Reilly

5.0k total citations · 1 hit paper
43 papers, 3.0k citations indexed

About

John F. Reilly is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, John F. Reilly has authored 43 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 9 papers in Pulmonary and Respiratory Medicine and 8 papers in Oncology. Recurrent topics in John F. Reilly's work include Fibroblast Growth Factor Research (6 papers), Lung Cancer Treatments and Mutations (5 papers) and PI3K/AKT/mTOR signaling in cancer (4 papers). John F. Reilly is often cited by papers focused on Fibroblast Growth Factor Research (6 papers), Lung Cancer Treatments and Mutations (5 papers) and PI3K/AKT/mTOR signaling in cancer (4 papers). John F. Reilly collaborates with scholars based in United States, United Kingdom and Spain. John F. Reilly's co-authors include Pamela Maher, Victoria M. Richon, Stanley R. Frankel, Cecilia Kelly, Xiao Ni, Justin L. Ricker, Parul Hazarika, Judy H. Chiao, Madeleine Duvic and Chunlei Zhang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Oncology.

In The Last Decade

John F. Reilly

41 papers receiving 2.9k citations

Hit Papers

Phase 2 trial of oral vor... 2006 2026 2012 2019 2006 250 500 750

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
John F. Reilly 1.8k 572 335 312 301 43 3.0k
Yoko Aoki 2.9k 1.6× 581 1.0× 255 0.8× 310 1.0× 254 0.8× 170 4.8k
Abner Louissaint 657 0.4× 481 0.8× 294 0.9× 106 0.3× 150 0.5× 55 2.1k
Grace Ku 929 0.5× 788 1.4× 282 0.8× 107 0.3× 456 1.5× 56 2.8k
Cory M. Johannessen 2.9k 1.6× 1.3k 2.3× 154 0.5× 432 1.4× 365 1.2× 28 4.2k
Benoît Bilanges 2.0k 1.1× 378 0.7× 349 1.0× 185 0.6× 183 0.6× 27 2.9k
Madan M. Kwatra 2.4k 1.3× 383 0.7× 213 0.6× 130 0.4× 386 1.3× 85 3.5k
Hideaki Yokoo 981 0.5× 338 0.6× 1000 3.0× 444 1.4× 178 0.6× 181 2.7k
Erik J. Uhlmann 1.7k 0.9× 734 1.3× 383 1.1× 589 1.9× 532 1.8× 73 3.4k
Jun Harada 1.3k 0.7× 264 0.5× 129 0.4× 147 0.5× 342 1.1× 63 2.5k
Julie Guillermet‐Guibert 2.3k 1.3× 956 1.7× 473 1.4× 316 1.0× 245 0.8× 53 3.9k

Countries citing papers authored by John F. Reilly

Since Specialization
Citations

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

Fields of papers citing papers by John F. Reilly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John F. Reilly. 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 John F. Reilly. The network helps show where John F. Reilly may publish in the future.

Co-authorship network of co-authors of John F. Reilly

This figure shows the co-authorship network connecting the top 25 collaborators of John F. Reilly. A scholar is included among the top collaborators of John F. Reilly 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 John F. Reilly. John F. Reilly 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.
Eftekharzadeh, Bahareh, et al.. (2024). Drug Discovery for Diseases with High Unmet Need Through Perturbation of Biomolecular Condensates. Journal of Molecular Biology. 436(23). 168855–168855. 1 indexed citations
2.
3.
Ledeboer, Mark W., Matthew H. Daniels, G. Malojcic, et al.. (2019). Discovery of a Potent and Selective TRPC5 Inhibitor, Efficacious in a Focal Segmental Glomerulosclerosis Model. ACS Medicinal Chemistry Letters. 10(11). 1579–1585. 44 indexed citations
4.
Morán, Teresa, Enriqueta Felip, Vicki L. Keedy, et al.. (2014). Activity of dalotuzumab, a selective anti-IGF1R antibody, in combination with erlotinib in unselected patients with Non-small-cell lung cancer: a phase I/II randomized trial. Experimental Hematology and Oncology. 3(1). 26–26. 27 indexed citations
5.
Benedettini, Elisa, Lynette M. Sholl, Michael Peyton, et al.. (2010). Met Activation in Non-Small Cell Lung Cancer Is Associated with de Novo Resistance to EGFR Inhibitors and the Development of Brain Metastasis. American Journal Of Pathology. 177(1). 415–423. 139 indexed citations
6.
Efferson, Clay L., Christopher T. Winkelmann, Christopher Ware, et al.. (2010). Downregulation of Notch Pathway by a γ-Secretase Inhibitor Attenuates AKT/Mammalian Target of Rapamycin Signaling and Glucose Uptake in an ERBB2 Transgenic Breast Cancer Model. Cancer Research. 70(6). 2476–2484. 76 indexed citations
7.
Galanis, Evanthia, Kurt A. Jaeckle, Matthew J. Maurer, et al.. (2009). Phase II Trial of Vorinostat in Recurrent Glioblastoma Multiforme: A North Central Cancer Treatment Group Study. Journal of Clinical Oncology. 27(12). 2052–2058. 283 indexed citations
8.
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
9.
Zhang, Weisheng, Joe Jiang Zhu, Clay L. Efferson, et al.. (2009). Inhibition of Tumor Growth Progression by Antiandrogens and mTOR Inhibitor in a Pten -Deficient Mouse Model of Prostate Cancer. Cancer Research. 69(18). 7466–7472. 66 indexed citations
10.
Haines, Brian B., Mélissa Chénard, Raquel Sevilla, et al.. (2009). A Quantitative Volumetric Micro-Computed Tomography Method to Analyze Lung Tumors in Genetically Engineered Mouse Models. Neoplasia. 11(1). 39–47. 36 indexed citations
11.
Fantin, Valeria R., Andrey Loboda, Cloud P. Paweletz, et al.. (2008). Constitutive Activation of Signal Transducers and Activators of Transcription Predicts Vorinostat Resistance in Cutaneous T-Cell Lymphoma. Cancer Research. 68(10). 3785–3794. 138 indexed citations
12.
Bloom, Floyd E., et al.. (2005). Mouse Models of Human Neurodegenerative Disorders. Archives of Neurology. 62(2). 185–185. 24 indexed citations
13.
Reilly, John F., Eiichi Mizukoshi, & Pamela Maher. (2004). Ligand Dependent and Independent Internalization and Nuclear Translocation of Fibroblast Growth Factor (FGF) Receptor 1. DNA and Cell Biology. 23(9). 538–548. 45 indexed citations
14.
Reilly, John F., et al.. (2004). High-throughput Morphometric Analysis of Individual Neurons. Cerebral Cortex. 14(5). 543–554. 33 indexed citations
15.
Reilly, John F., et al.. (2000). Association of Fibroblast Growth Factor Receptor 1 with the Adaptor Protein Grb14. Journal of Biological Chemistry. 275(11). 7771–7778. 57 indexed citations
16.
Bain, Barbara J., R. Amos, D. Bareford, et al.. (1998). THE LABORATORY DIAGNOSIS OF HAEMOGLOBINOPATHIES. British Journal of Haematology. 101(4). 783–792. 102 indexed citations
17.
Reilly, John F., Pamela Maher, & Vijaya Kumari. (1998). Regulation of astrocyte GFAP expression by TGF-?1 and FGF-2. Glia. 22(2). 202–210. 91 indexed citations
18.
Reilly, John F., et al.. (1997). Heparan sulfate modifies the effects of basic fibroblast growth factor on glial reactivity. Brain Research. 759(2). 277–284. 6 indexed citations
19.
Singletary, Eunice M. & John F. Reilly. (1990). Acute frontal sinus barotrauma. The American Journal of Emergency Medicine. 8(4). 329–331. 6 indexed citations
20.
Reilly, John F.. (1981). Hospital Cost Containment: Selected Notes for Future Policy. PubMed Central. 57(5). 405–406. 2 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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