Charles Prussak

1.3k total citations
35 papers, 1.0k citations indexed

About

Charles Prussak is a scholar working on Genetics, Molecular Biology and Immunology. According to data from OpenAlex, Charles Prussak has authored 35 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Genetics, 15 papers in Molecular Biology and 12 papers in Immunology. Recurrent topics in Charles Prussak's work include Chronic Lymphocytic Leukemia Research (16 papers), Monoclonal and Polyclonal Antibodies Research (10 papers) and CAR-T cell therapy research (5 papers). Charles Prussak is often cited by papers focused on Chronic Lymphocytic Leukemia Research (16 papers), Monoclonal and Polyclonal Antibodies Research (10 papers) and CAR-T cell therapy research (5 papers). Charles Prussak collaborates with scholars based in United States, Japan and Germany. Charles Prussak's co-authors include Thomas J. Kipps, Laura Z. Rassenti, Mark J. Cantwell, William G. Wierda, Ben Tseng, George F. Widhopf, Januario E. Castro, Dennis A. Carson, Liguang Chen and Li Tang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Charles Prussak

34 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Charles Prussak United States 12 564 378 360 312 144 35 1.0k
Roland Geisberger Austria 18 388 0.7× 526 1.4× 417 1.2× 184 0.6× 128 0.9× 49 1.1k
Erica N Evans United States 19 487 0.9× 379 1.0× 187 0.5× 288 0.9× 191 1.3× 44 1.2k
Sergio Roa United States 19 700 1.2× 601 1.6× 226 0.6× 241 0.8× 322 2.2× 35 1.3k
David Siwarski United States 17 602 1.1× 397 1.1× 442 1.2× 87 0.3× 155 1.1× 41 1.1k
Russell Karp United States 11 374 0.7× 210 0.6× 196 0.5× 174 0.6× 105 0.7× 16 711
Kevin T. Merrell United States 14 588 1.0× 761 2.0× 170 0.5× 128 0.4× 92 0.6× 17 1.4k
James D. Owens United States 12 445 0.8× 306 0.8× 161 0.4× 114 0.4× 145 1.0× 27 845
Hina S. Maniar United States 12 332 0.6× 534 1.4× 108 0.3× 216 0.7× 57 0.4× 15 882
Melanie Cornejo United States 11 1.0k 1.8× 390 1.0× 381 1.1× 150 0.5× 96 0.7× 19 1.6k
Konrad Miatkowski United States 13 1.0k 1.8× 529 1.4× 192 0.5× 120 0.4× 75 0.5× 16 1.6k

Countries citing papers authored by Charles Prussak

Since Specialization
Citations

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

Fields of papers citing papers by Charles Prussak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Charles Prussak

This figure shows the co-authorship network connecting the top 25 collaborators of Charles Prussak. A scholar is included among the top collaborators of Charles Prussak 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 Charles Prussak. Charles Prussak 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.
Prussak, Charles, Sharon Lam, Jieyu Zhang, et al.. (2020). Preclinical evaluation of anti-ROR1 CAR T cells employing a ROR1 binding SCFV derived from the clinical stage mab cirmtuzumab.. Journal of Clinical Oncology. 38(5_suppl). 41–41. 2 indexed citations
2.
Choi, Michael Y., George F. Widhopf, Emanuela M. Ghia, et al.. (2018). Phase I Trial: Cirmtuzumab Inhibits ROR1 Signaling and Stemness Signatures in Patients with Chronic Lymphocytic Leukemia. Cell stem cell. 22(6). 951–959.e3. 144 indexed citations
3.
Choi, Michael Y., Catriona Jamieson, George F. Widhopf, et al.. (2016). A Phase 1 Clinical Trial of Cirmtuzumab, a First-in-Class ROR1 Inhibiting Antibody, for the Treatment of Patients with Relapsed or Refractory CLL: Interim Analysis. Clinical Lymphoma Myeloma & Leukemia. 16. S44–S44. 1 indexed citations
4.
5.
Choi, Michael Y., George F. Widhopf, Christina Wu, et al.. (2015). Pre-clinical Specificity and Safety of UC-961, a First-In-Class Monoclonal Antibody Targeting ROR1. Clinical Lymphoma Myeloma & Leukemia. 15. S167–S169. 98 indexed citations
6.
Cui, Bing, George F. Widhopf, Charles Prussak, et al.. (2013). Cirmtuzumab Vedotin (UC-961ADC3), An Anti-ROR1-Monomethyl Auristatin E Antibody-Drug Conjugate, Is a Potential Treatment For ROR1-Positive Leukemia and Solid Tumors. Blood. 122(21). 1637–1637. 11 indexed citations
7.
Sadarangani, Anil, George F. Widhopf, Charles Prussak, et al.. (2012). A Highly Selective Anti-ROR1 Monoclonal Antibody Inhibits Human Acute Myeloid Leukemia CD34+ Cell Survival and Self-Renewal.. Blood. 120(21). 2560–2560. 3 indexed citations
8.
Zhang, Suping, Christina Wu, Bing Cui, et al.. (2011). A Monoclonal Antibody Specifically Targeting CD44 Inhibits B-Cell Chronic Lymphocytic Leukemia Cell Survival In Vitro and In Vivo. Blood. 118(21). 927–927. 2 indexed citations
9.
Wierda, William G., Januario E. Castro, Deepa Sampath, et al.. (2010). A phase I study of immune gene therapy for patients with CLL using a membrane-stable, humanized CD154. Leukemia. 24(11). 1893–1900. 36 indexed citations
10.
Castro, Januario E., Jose Sandoval‐Sus, Johanna Melo‐Cardenas, et al.. (2009). Phase I study of intranodal direct injection of adenovirus encoding recombinant CD40-ligand (Ad-ISF35) in patients with chronic lymphocytic leukemia. Journal of Clinical Oncology. 27(15_suppl). 3003–3003. 1 indexed citations
11.
Rieger, R., David C. Whitacre, Mark J. Cantwell, Charles Prussak, & Thomas J. Kipps. (2008). Chimeric form of tumor necrosis factor-α has enhanced surface expression and antitumor activity. Cancer Gene Therapy. 16(1). 53–64. 6 indexed citations
12.
13.
Whitacre, David C., Farah Hedjran, Ingo G.H. Schmidt‐Wolf, et al.. (2005). Highly Efficient Gene-Transfer into Chronic Lymphocytic Leukemia Cells Using Adenovirus Type 35 Genetic Vectors.. Blood. 106(11). 2109–2109. 1 indexed citations
14.
Wierda, William G., et al.. (2000). CD40-ligand (CD154) gene therapy for chronic lymphocytic leukemia. Blood. 96(9). 2917–2924. 16 indexed citations
15.
Wierda, William G., et al.. (2000). CD40-ligand (CD154) gene therapy for chronic lymphocytic leukemia. Blood. 96(9). 2917–2924. 272 indexed citations
16.
17.
Prussak, Charles, et al.. (1989). Peptide production from proteins separated by sodium dodecyl-sulfate polyacrylamide gel electrophoresis. Analytical Biochemistry. 178(2). 233–238. 28 indexed citations
18.
Tseng, Ben & Charles Prussak. (1989). Sequence and structural requirements for primase initiation in the SV40 origin of replication. Nucleic Acids Research. 17(5). 1953–1963. 10 indexed citations
19.
Prussak, Charles & Ben Tseng. (1989). DNA polymerase alpha activity is not affected by protein kinases or alkaline phosphatase. Biochemical and Biophysical Research Communications. 159(3). 1397–1403. 5 indexed citations
20.
Prussak, Charles, et al.. (1989). Mouse Primase p49 Subunit Molecular Cloning Indicates Conserved and Divergent Regions. Journal of Biological Chemistry. 264(9). 4957–4963. 38 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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