Gail Bukofzer

613 total citations
17 papers, 396 citations indexed

About

Gail Bukofzer is a scholar working on Oncology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Gail Bukofzer has authored 17 papers receiving a total of 396 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Oncology, 6 papers in Molecular Biology and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Gail Bukofzer's work include Iron Metabolism and Disorders (5 papers), Monoclonal and Polyclonal Antibodies Research (4 papers) and Immunotherapy and Immune Responses (3 papers). Gail Bukofzer is often cited by papers focused on Iron Metabolism and Disorders (5 papers), Monoclonal and Polyclonal Antibodies Research (4 papers) and Immunotherapy and Immune Responses (3 papers). Gail Bukofzer collaborates with scholars based in United States, South Africa and United Kingdom. Gail Bukofzer's co-authors include W. Edward Swords, Jessica L. VonCannon, Michael J. Mitten, Cherrie K. Donawho, Joann P. Palma, Luis E. Rodrı́guez, T. H. Bothwell, Vincent L. Giranda, Yichun Wang and Debra Montgomery and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Cancer Research.

In The Last Decade

Gail Bukofzer

17 papers receiving 389 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gail Bukofzer United States 8 185 166 85 66 48 17 396
Natalia D. Tararova United States 7 277 1.5× 156 0.9× 58 0.7× 46 0.7× 60 1.3× 9 473
Debbie Nahas United States 9 323 1.7× 56 0.3× 36 0.4× 96 1.5× 15 0.3× 15 512
Kazunori Namiki United States 6 173 0.9× 58 0.3× 89 1.0× 56 0.8× 24 0.5× 8 339
Koichi Sawaki Japan 15 207 1.1× 119 0.7× 105 1.2× 30 0.5× 120 2.5× 37 495
Zesheng Wan United States 8 276 1.5× 162 1.0× 22 0.3× 22 0.3× 23 0.5× 12 528
Baharak Khadang Italy 10 210 1.1× 132 0.8× 9 0.1× 115 1.7× 24 0.5× 13 474
Marie‐Louise Zani France 9 200 1.1× 71 0.4× 27 0.3× 27 0.4× 83 1.7× 9 436
F Ghani United States 4 170 0.9× 96 0.6× 13 0.2× 35 0.5× 44 0.9× 8 397
Venkata Ramana Doppalapudi United States 14 334 1.8× 102 0.6× 14 0.2× 43 0.7× 25 0.5× 21 626
A. Pennings Netherlands 12 215 1.2× 66 0.4× 20 0.2× 17 0.3× 12 0.3× 25 452

Countries citing papers authored by Gail Bukofzer

Since Specialization
Citations

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

Fields of papers citing papers by Gail Bukofzer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gail Bukofzer

This figure shows the co-authorship network connecting the top 25 collaborators of Gail Bukofzer. A scholar is included among the top collaborators of Gail Bukofzer 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 Gail Bukofzer. Gail Bukofzer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Chervin, Adam S., Jennifer D. Stone, Iwona Konieczna, et al.. (2023). ABBV-184: A Novel Survivin-specific TCR/CD3 Bispecific T-cell Engager is Active against Both Solid Tumor and Hematologic Malignancies. Molecular Cancer Therapeutics. 22(8). 903–912. 7 indexed citations
2.
Guo, Jun, Xiao Yu, Xin Lü, et al.. (2019). Empowering therapeutic antibodies with IFN-α for cancer immunotherapy. PLoS ONE. 14(8). e0219829–e0219829. 20 indexed citations
3.
Guo, Jun, Xiao Yu, Marc Lake, et al.. (2018). Abstract 2783: Empowering therapeutic monoclonal antibodies with IFN-alpha for cancer immunotherapy. Cancer Research. 78(13_Supplement). 2783–2783. 1 indexed citations
4.
Bardwell, Philip D., Matthew Staron, Junjian Liu, et al.. (2017). Potent and conditional redirected T cell killing of tumor cells using Half DVD-Ig. Protein & Cell. 9(1). 121–129. 11 indexed citations
5.
Wang, Yichun, Luis E. Rodrı́guez, Paul A. Ellis, et al.. (2012). Abstract 858: Potent in vivo activity of the aurora kinase inhibitor ABT-348 in human acute myeloid leukemia and myelodysplastic syndrome xenograft models. Cancer Research. 72(8_Supplement). 858–858. 1 indexed citations
6.
Mudd, Sarah R., Martin J. Voorbach, Todd Cole, et al.. (2011). Pharmacodynamic Evaluation of Irinotecan Therapy by FDG and FLT PET/CT Imaging in a Colorectal Cancer Xenograft Model. Molecular Imaging and Biology. 14(5). 617–624. 17 indexed citations
7.
Palma, Joann P., Yichun Wang, Luis E. Rodrı́guez, et al.. (2009). ABT-888 Confers Broad In vivo Activity in Combination with Temozolomide in Diverse Tumors. Clinical Cancer Research. 15(23). 7277–7290. 111 indexed citations
8.
Frey, Robin R., Michael L. Curtin, Daniel H. Albert, et al.. (2008). 7-Aminopyrazolo[1,5-a]pyrimidines as Potent Multitargeted Receptor Tyrosine Kinase Inhibitors. Journal of Medicinal Chemistry. 51(13). 3777–3787. 42 indexed citations
9.
Wang, Jieyi, Lora A. Tucker, Jason Stavropoulos, et al.. (2008). Correlation of tumor growth suppression and methionine aminopetidase-2 activity blockade using an orally active inhibitor. Proceedings of the National Academy of Sciences. 105(6). 1838–1843. 25 indexed citations
10.
Donawho, Cherrie K., Jonathan A. Hickson, Yichun Wang, et al.. (2007). The RTK inhibitor ABT-869, alone and in combination with paclitaxel and/or zoledronic acid, demonstrates significant reduction in the development of both osteoblastic (LuCap 23.1) and osteolytic (PC3-M-Luciferase) tumors intratibially. Molecular Cancer Therapeutics. 6. 2 indexed citations
11.
Donawho, Cherrie K., Yichun Wang, Gail Bukofzer, et al.. (2007). The RTK inhibitor, ABT-869 alone or in combination with various cytotoxic therapies demonstrate significant tumor growth inhibition in orthotopic hepatocellular carcinoma, renal cell carcinoma and prostate xenografts. Molecular Cancer Therapeutics. 6. 1 indexed citations
12.
Swords, W. Edward, et al.. (2003). Sialylation of Lipooligosaccharides Promotes Biofilm Formation by Nontypeable Haemophilus influenzae. Infection and Immunity. 72(1). 106–113. 115 indexed citations
13.
Baynes, Roy D., et al.. (1989). Iron metabolism in normal and hemochromatotic macrophages. American Journal of Hematology. 31(1). 21–25. 5 indexed citations
14.
Baynes, Roy D., et al.. (1988). Effect of ferrous and ferric chelators on transferrin‐iron‐macrophage interactions. American Journal of Hematology. 29(1). 27–32. 5 indexed citations
15.
Baynes, Roy, B Friedman, Lynne McNamara, et al.. (1988). Transferrin iron interactions with cultured hepatocellular carcinoma cells (PLC/PRF/5).. PubMed. 46(2). 282–8. 6 indexed citations
16.
Baynes, Roy, Gail Bukofzer, T. H. Bothwell, W. R. Bezwoda, & B Macfarlane. (1987). Transferrin receptors and transferrin iron uptake by cultured human blood monocytes.. PubMed. 43(3). 372–6. 20 indexed citations
17.
Baynes, Roy D., Gail Bukofzer, T. H. Bothwell, & W. R. Bezwoda. (1987). Apotransferrin receptors and the delivery of iron from cultured human blood monocytes. American Journal of Hematology. 25(4). 417–425. 7 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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