Michael E. Williams

7.3k total citations
111 papers, 3.3k citations indexed

About

Michael E. Williams is a scholar working on Pathology and Forensic Medicine, Genetics and Oncology. According to data from OpenAlex, Michael E. Williams has authored 111 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Pathology and Forensic Medicine, 50 papers in Genetics and 38 papers in Oncology. Recurrent topics in Michael E. Williams's work include Lymphoma Diagnosis and Treatment (53 papers), Chronic Lymphocytic Leukemia Research (46 papers) and Viral-associated cancers and disorders (12 papers). Michael E. Williams is often cited by papers focused on Lymphoma Diagnosis and Treatment (53 papers), Chronic Lymphocytic Leukemia Research (46 papers) and Viral-associated cancers and disorders (12 papers). Michael E. Williams collaborates with scholars based in United States, Canada and United Kingdom. Michael E. Williams's co-authors include Michael F. Jarvis, Geoffrey Burnstock, Steven H. Swerdlow, Ronald P. Taylor, Margaret A. Lindorfer, Adam D. Kennedy, Paul V. Beum, John Densmore, Brad S. Kahl and Charles E. Hess and has published in prestigious journals such as Journal of Clinical Investigation, Journal of Clinical Oncology and Physical review. B, Condensed matter.

In The Last Decade

Michael E. Williams

103 papers receiving 3.2k citations

Author Peers

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

Author Last Decade Papers Cites
Michael E. Williams 1.2k 1.1k 943 897 624 111 3.3k
Akio Asai 396 0.3× 902 0.9× 842 0.9× 2.3k 2.6× 433 0.7× 144 4.5k
Kai Cao 389 0.3× 1.2k 1.1× 919 1.0× 1.2k 1.3× 2.0k 3.2× 196 5.9k
Giuseppe A. Palumbo 500 0.4× 922 0.9× 1.1k 1.1× 1.6k 1.8× 1.1k 1.7× 216 4.2k
Vittorio Rosti 348 0.3× 579 0.5× 2.3k 2.4× 2.4k 2.6× 707 1.1× 188 6.2k
Eric Larsen 356 0.3× 668 0.6× 175 0.2× 1.1k 1.2× 353 0.6× 100 4.3k
Antonio Paolo Beltrami 514 0.4× 735 0.7× 2.6k 2.7× 5.2k 5.8× 512 0.8× 134 9.5k
Jiliang Li 333 0.3× 1.9k 1.8× 359 0.4× 5.4k 6.0× 430 0.7× 120 8.2k
F. Richard Bringhurst 422 0.3× 2.4k 2.2× 978 1.0× 3.4k 3.8× 733 1.2× 75 6.6k
Daniela Cesselli 244 0.2× 620 0.6× 952 1.0× 2.5k 2.7× 371 0.6× 110 4.7k
Eiichi Ishikawa 236 0.2× 881 0.8× 1.1k 1.2× 553 0.6× 1.0k 1.6× 321 3.9k

Countries citing papers authored by Michael E. Williams

Since Specialization
Citations

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

Fields of papers citing papers by Michael E. Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael E. Williams. 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 Michael E. Williams. The network helps show where Michael E. Williams may publish in the future.

Co-authorship network of co-authors of Michael E. Williams

This figure shows the co-authorship network connecting the top 25 collaborators of Michael E. Williams. A scholar is included among the top collaborators of Michael E. Williams 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 Michael E. Williams. Michael E. Williams 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.
Williams, Michael E., et al.. (2025). Pannexins in the vasculature. American Journal of Physiology-Heart and Circulatory Physiology. 329(6). H1449–H1470.
2.
Williams, Michael E., et al.. (2025). Exploring the role of EMT in ovarian cancer progression using a multiscale mathematical model. npj Systems Biology and Applications. 11(1). 36–36.
3.
4.
Yin, Qing, Michelle Wang, Allen Hu, et al.. (2024). Combinatorial Therapy of CDK9 Inhibitor with CD19 CAR-T to Reciprocally Overcome Therapy Resistance and Enhance Treatment Efficacies Against Aggressive B-Cell Lymphomas. Blood. 144(Supplement 1). 6219–6219. 1 indexed citations
5.
6.
Jayappa, Kallesh D., Vicki L. Gordon, Christopher G. Morris, et al.. (2021). Extrinsic interactions in the microenvironment in vivo activate an antiapoptotic multidrug-resistant phenotype in CLL. Blood Advances. 5(17). 3497–3510. 13 indexed citations
7.
Jayappa, Kallesh D., Craig A. Portell, Vicki L. Gordon, et al.. (2017). Microenvironmental agonists generate de novo phenotypic resistance to combined ibrutinib plus venetoclax in CLL and MCL. Blood Advances. 1(14). 933–946. 81 indexed citations
8.
Williams, Michael E.. (2017). CAR-T Cell Therapy for Chronic Lymphocytic Leukemia. Journal watch. 2017. 1 indexed citations
9.
10.
Williams, Michael E., Joseph M. Connors, Martin Dreyling, et al.. (2010). Mantle cell lymphoma: report of the 2010 Mantle Cell Lymphoma Consortium Workshop. Leukemia & lymphoma. 52(1). 24–33. 14 indexed citations
11.
Li, Yongli, Michael E. Williams, John B. Cousar, et al.. (2007). Rituximab-CD20 Complexes Are Shaved from Z138 Mantle Cell Lymphoma Cells in Intravenous and Subcutaneous SCID Mouse Models. The Journal of Immunology. 179(6). 4263–4271. 50 indexed citations
12.
Williams, Michael E.. (2006). Clonal Evolution in Chronic Lymphocytic Leukemia. Journal watch. 2006.
13.
Williams, Michael E., John Densmore, Andrew W. Pawluczkowycz, et al.. (2006). Thrice-Weekly Low-Dose Rituximab Decreases CD20 Loss via Shaving and Promotes Enhanced Targeting in Chronic Lymphocytic Leukemia. The Journal of Immunology. 177(10). 7435–7443. 124 indexed citations
14.
Beum, Paul V., Adam D. Kennedy, Michael E. Williams, Margaret A. Lindorfer, & Ronald P. Taylor. (2006). The Shaving Reaction: Rituximab/CD20 Complexes Are Removed from Mantle Cell Lymphoma and Chronic Lymphocytic Leukemia Cells by THP-1 Monocytes. The Journal of Immunology. 176(4). 2600–2609. 168 indexed citations
15.
Kennedy, Adam D., Paul V. Beum, Michael D. Solga, et al.. (2004). Rituximab Infusion Promotes Rapid Complement Depletion and Acute CD20 Loss in Chronic Lymphocytic Leukemia. The Journal of Immunology. 172(5). 3280–3288. 276 indexed citations
16.
Boyle, D L, Elizabeth A. Kowaluk, Michael F. Jarvis, et al.. (2001). Anti-Inflammatory Effects of ABT-702, a Novel Non-Nucleoside Adenosine Kinase Inhibitor, in Rat Adjuvant Arthritis. Journal of Pharmacology and Experimental Therapeutics. 296(2). 495–500. 40 indexed citations
17.
Mandell, James W., Margaret L. Gulley, Michael E. Williams, & Mark H. Stoler. (1999). Recurrent epstein-barr virus-associated post-transplant lymphoproliferative disorder: Report of a patient with histologically similar but clonally distinct metachronous abdominal and brain lesions. Human Pathology. 30(10). 1262–1265. 5 indexed citations
18.
Williams, Michael E., Guy E. Nichols, Steven H. Swerdlow, & Mark H. Stoler. (1995). In situ hybridization detection of cyclin Dl mRNA in centrocytic/mantle cell lymphoma. Annals of Oncology. 6(3). 297–299. 26 indexed citations
19.
Macon, William R., Michael E. Williams, John P. Greer, & John B. Cousar. (1995). Paracortical Nodular T-Cell Lymphoma. The American Journal of Surgical Pathology. 19(3). 297–303. 23 indexed citations
20.
Williams, Michael E. & Steven H. Swerdlow. (1994). Cyclin D1 overexpression in non-Hodgkin's lymphoma with chromosome 11 bcl-1 rearrangement. Annals of Oncology. 5. S71–S73. 46 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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