Lee Silverman

3.2k total citations
26 papers, 773 citations indexed

About

Lee Silverman is a scholar working on Cell Biology, Immunology and Oncology. According to data from OpenAlex, Lee Silverman has authored 26 papers receiving a total of 773 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cell Biology, 7 papers in Immunology and 6 papers in Oncology. Recurrent topics in Lee Silverman's work include T-cell and Retrovirus Studies (5 papers), Animal Disease Management and Epidemiology (5 papers) and Vector-Borne Animal Diseases (5 papers). Lee Silverman is often cited by papers focused on T-cell and Retrovirus Studies (5 papers), Animal Disease Management and Epidemiology (5 papers) and Vector-Borne Animal Diseases (5 papers). Lee Silverman collaborates with scholars based in United States, Spain and Japan. Lee Silverman's co-authors include Michael D. Lairmore, Lee Ratner, Andrew J. Phipps, Mark Manfredi, David A. Janowick, Todd B. Sells, Jeffrey Ecsedy, Kara M. Hoar, Mengkun Zhang and Deborah R. Wysong and has published in prestigious journals such as Blood, Cancer Research and Oncogene.

In The Last Decade

Lee Silverman

26 papers receiving 757 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lee Silverman United States 15 288 234 226 203 178 26 773
Joëlle Kersual France 8 302 1.0× 350 1.5× 57 0.3× 45 0.2× 116 0.7× 12 695
J Dittmer United States 11 253 0.9× 202 0.9× 105 0.5× 19 0.1× 125 0.7× 14 575
Julie C. Watt United States 9 382 1.3× 110 0.5× 136 0.6× 34 0.2× 39 0.2× 10 520
Shingo Toji Japan 14 670 2.3× 253 1.1× 286 1.3× 217 1.1× 63 0.4× 25 1.0k
Oekyung Kim United States 13 611 2.1× 114 0.5× 205 0.9× 129 0.6× 56 0.3× 17 1.2k
H Hirai Japan 16 596 2.1× 227 1.0× 332 1.5× 94 0.5× 9 0.1× 36 1.1k
Jonathan C. Betts United States 9 727 2.5× 404 1.7× 355 1.6× 64 0.3× 19 0.1× 10 1.2k
N K Bhat United States 16 762 2.6× 291 1.2× 201 0.9× 32 0.2× 23 0.1× 22 1.1k
Christine E. Seyfried United States 11 336 1.2× 435 1.9× 47 0.2× 91 0.4× 19 0.1× 13 897
T W Flickinger United States 11 573 2.0× 358 1.5× 559 2.5× 36 0.2× 11 0.1× 11 1.0k

Countries citing papers authored by Lee Silverman

Since Specialization
Citations

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

Fields of papers citing papers by Lee Silverman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lee Silverman

This figure shows the co-authorship network connecting the top 25 collaborators of Lee Silverman. A scholar is included among the top collaborators of Lee Silverman 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 Lee Silverman. Lee Silverman 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.
Nagaraja, Raj, Andrew Olaharski, Rohini Narayanaswamy, et al.. (2020). Preclinical toxicology profile of squalene epoxidase inhibitors. Toxicology and Applied Pharmacology. 401. 115103–115103. 17 indexed citations
2.
3.
Chan, Barden, Michelle Clasquin, Gromoslaw A. Smolen, et al.. (2016). A mouse model of a human congenital disorder of glycosylation caused by loss of PMM2. Human Molecular Genetics. 25(11). 2182–2193. 33 indexed citations
4.
Chubukov, Victor, Kendall Johnson, Penelope A. Kosinski, et al.. (2016). Characterization of Metabolic Response to AG-348, an Allosteric Activator of Red Cell Pyruvate Kinase, in Healthy Volunteers and Pyruvate Kinase Deficiency Patients. Blood. 128(22). 2452–2452. 1 indexed citations
5.
Kung, Charles, Collin Hill, Yue Chen, et al.. (2014). AG-348 Activation of Pyruvate Kinase in Vivo Enhances Red Cell Glycolysis in Mice. Blood. 124(21). 4010–4010. 1 indexed citations
6.
Manfredi, Mark, Jeffrey Ecsedy, Arijit Chakravarty, et al.. (2011). Characterization of Alisertib (MLN8237), an Investigational Small-Molecule Inhibitor of Aurora A Kinase Using Novel In Vivo Pharmacodynamic Assays. Clinical Cancer Research. 17(24). 7614–7624. 242 indexed citations
7.
Alden, Carl L., Andrew M. Lynn, Daniel Morton, et al.. (2011). A Critical Review of the Effectiveness of Rodent Pharmaceutical Carcinogenesis Testing in Predicting for Human Risk. Veterinary Pathology. 48(3). 772–784. 35 indexed citations
8.
Bruna, Jordi, Esther Udina, Albert Alé, et al.. (2010). Neurophysiological, histological and immunohistochemical characterization of bortezomib-induced neuropathy in mice. Experimental Neurology. 223(2). 599–608. 83 indexed citations
9.
Maziasz, Timothy J., Vivek J. Kadambi, Lee Silverman, Eric R. Fedyk, & Carl L. Alden. (2010). Predictive Toxicology Approaches for Small Molecule Oncology Drugs. Toxicologic Pathology. 38(1). 148–164. 10 indexed citations
10.
Csizmadia, Vilmos, Eva Csizmadia, Lee Silverman, et al.. (2010). Effect of Proteasome Inhibitors With Different Chemical Structures on the Ubiquitin–Proteasome System In Vitro. Veterinary Pathology. 47(2). 358–367. 16 indexed citations
11.
12.
Sells, Todd B., Jeffrey Ecsedy, Stephen G. Stroud, et al.. (2008). MLN8237: an orally active small molecule inhibitor of Aurora A kinase in phase I clinical trials. Cancer Research. 68. 237–237. 14 indexed citations
13.
Chakravarty, Arijit, Vaishali Shinde, Katherine Galvin, et al.. (2008). 93 POSTER Phase I assessment of mechanistic pharmacodynamic biomarkers for MLN8054, a small-molecule inhibitor of Aurora A kinase. European Journal of Cancer Supplements. 6(12). 32–32. 2 indexed citations
14.
15.
Datta, Antara, Lee Silverman, Andrew J. Phipps, et al.. (2007). Human T-lymphotropic virus type-1 p30 alters cell cycle G2 regulation of T lymphocytes to enhance cell survival. Retrovirology. 4(1). 49–49. 28 indexed citations
16.
Silverman, Lee, Andrew J. Phipps, Soledad Fernández, et al.. (2005). In vivo analysis of replication and immunogenicity of proviral clones of human T-lymphotropic virus type 1 with selective envelope surface-unit mutations. Blood. 106(10). 3602–3608. 11 indexed citations
17.
Lairmore, Michael D., Lee Silverman, & Lee Ratner. (2005). Animal models for human T-lymphotropic virus type 1 (HTLV-1) infection and transformation. Oncogene. 24(39). 6005–6015. 51 indexed citations
18.
Silverman, Lee, et al.. (2004). Enhanced expression of Cyclooxygenase‐2 in glaucomatous dog eyes. Veterinary Ophthalmology. 7(1). 59–62. 14 indexed citations
19.
Ye, Jianxin, Lee Silverman, Michael D. Lairmore, & Patrick L. Green. (2003). HTLV-1 Rex is required for viral spread and persistence in vivo but is dispensable for cellular immortalization in vitro. Blood. 102(12). 3963–3969. 48 indexed citations
20.
Khan, Kanwar Nasir M., et al.. (1999). Paratrichial Sweat Gland Adenocarcinoma in a Marmoset. Journal of Veterinary Diagnostic Investigation. 11(5). 478–480. 6 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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