P. Mickey Williams

12.9k total citations · 3 hit papers
86 papers, 7.0k citations indexed

About

P. Mickey Williams is a scholar working on Molecular Biology, Cancer Research and Pulmonary and Respiratory Medicine. According to data from OpenAlex, P. Mickey Williams has authored 86 papers receiving a total of 7.0k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Molecular Biology, 36 papers in Cancer Research and 28 papers in Pulmonary and Respiratory Medicine. Recurrent topics in P. Mickey Williams's work include Cancer Genomics and Diagnostics (32 papers), Molecular Biology Techniques and Applications (16 papers) and Lung Cancer Treatments and Mutations (13 papers). P. Mickey Williams is often cited by papers focused on Cancer Genomics and Diagnostics (32 papers), Molecular Biology Techniques and Applications (16 papers) and Lung Cancer Treatments and Mutations (13 papers). P. Mickey Williams collaborates with scholars based in United States, Malaysia and Canada. P. Mickey Williams's co-authors include Robert Soriano, Thomas D. Wu, Heidi Phillips, Samir Kharbanda, Ken Aldape, Anjan Misra, Janice Nigro, Howard Colman, Zora Modrušan and William F. Forrest and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

P. Mickey Williams

75 papers receiving 6.8k citations

Hit Papers

Molecular subclasses of high-grade glioma predict prognos... 1996 2026 2006 2016 2006 1996 2021 500 1000 1.5k 2.0k

Peers

P. Mickey Williams
Fei Huang China
Chao Lü United States
Matthew J. Walter United States
Jun Dong China
Alexei Protopopov United States
P. Mickey Williams
Citations per year, relative to P. Mickey Williams P. Mickey Williams (= 1×) peers Raffaele Calogero

Countries citing papers authored by P. Mickey Williams

Since Specialization
Citations

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

Fields of papers citing papers by P. Mickey Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of P. Mickey Williams

This figure shows the co-authorship network connecting the top 25 collaborators of P. Mickey Williams. A scholar is included among the top collaborators of P. Mickey 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 P. Mickey Williams. P. Mickey 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.
Gouda, Mohamed A., Filip Jankú, Ying Yuan, et al.. (2025). Concordance between Tumor Tissue and Plasma DNA Genotyping in the NCI-MATCH Trial (EAY131). Clinical Cancer Research. 31(20). 4299–4310. 1 indexed citations
2.
McCourt, Carolyn K., Zihan Wei, Kevin Kalinsky, et al.. (2025). Ipatasertib in Patients with Tumors with AKT Mutations: Results from the NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocol Z1K. Clinical Cancer Research. 31(23). 4912–4919. 2 indexed citations
3.
Gettinger, Scott, Karen L. Reckamp, Jeffrey A. Moscow, et al.. (2024). Phase II Trial of Afatinib in Patients With EGFR-Mutated Solid Tumors Excluding Lung Cancer: Results From NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocol A. JCO Precision Oncology. 8(8). e2300725–e2300725. 2 indexed citations
4.
Kaluziak, Stefan T., Beatrice Melli, Lisa M. McShane, et al.. (2024). Discovery of Gene Fusions in Driver-Negative Cancer Samples From the National Cancer Institute-Molecular Analysis for Therapy Choice Screening Cohort. JCO Precision Oncology. 8(8). e2400493–e2400493.
5.
O’Hara, Mark H., Opeyemi A. Jegede, Mark A. Dickson, et al.. (2024). Phase II Study of Palbociclib in Patients with Tumors with CDK4 or CDK6 Amplification: Results from the NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocol Z1C. Clinical Cancer Research. 31(1). 56–64. 1 indexed citations
6.
Karlovich, Chris, Jennifer L. Silhavy, Biswajit Das, et al.. (2023). Blood-based assessment of patients with mismatch repair-deficient tumors enrolled in NCI-MATCH Arm Z1D (nivolumab).. Journal of Clinical Oncology. 41(16_suppl). 2560–2560.
7.
Das, Biswajit, Sorena Rahmanian, Jennifer L. Silhavy, et al.. (2023). Molecular profiling of ctDNA from NCI-MATCH patients enrolled for treatment with mTOR1/2 inhibitor sapanisertib (arm M) and the Hedgehog pathway inhibitor vismodegib (arm T).. Journal of Clinical Oncology. 41(16_suppl). 3047–3047. 1 indexed citations
8.
Williams, P. Mickey, Steven P. Lund, Kenneth D. Cole, et al.. (2021). Validation of ctDNA Quality Control Materials Through a Precompetitive Collaboration of the Foundation for the National Institutes of Health. JCO Precision Oncology. 5(5). 910–920. 14 indexed citations
9.
Connolly, Roisín M., Petros Grivas, Edith P. Mitchell, et al.. (2020). 553P Activity of trastuzumab and pertuzumab (HP) in patients with non-breast/gastroesophgeal HER2-amplified tumours: Results of the NCI-MATCH trial (EAY131) subprotocol J. Annals of Oncology. 31. S479–S480. 2 indexed citations
10.
Karlovich, Chris & P. Mickey Williams. (2019). Clinical Applications of Next-Generation Sequencing in Precision Oncology. The Cancer Journal. 25(4). 264–271. 25 indexed citations
11.
Lih, Chih‐Jian, Han Si, Biswajit Das, et al.. (2016). Certified DNA Reference Materials to Compare HER2 Gene Amplification Measurements Using Next-Generation Sequencing Methods. Journal of Molecular Diagnostics. 18(5). 753–761. 12 indexed citations
12.
McShane, Lisa M., Margaret M. Cavenagh, Tracy Lively, et al.. (2013). Criteria for the use of omics-based predictors in clinical trials. Nature. 502(7471). 317–320. 164 indexed citations
13.
Williams, P. Mickey, et al.. (2010). A Novel Method of Amplification of FFPET-Derived RNA Enables Accurate Disease Classification with Microarrays. Journal of Molecular Diagnostics. 12(5). 680–686. 41 indexed citations
14.
Fu, Ling, Linu M. John, Sean H. Adams, et al.. (2004). Fibroblast Growth Factor 19 Increases Metabolic Rate and Reverses Dietary and Leptin-Deficient Diabetes. Endocrinology. 145(6). 2594–2603. 481 indexed citations
15.
Williams, Stephen J. & P. Mickey Williams. (2003). Quantitation of mRNA by Competitive PCR Using Capillary Electrophoresis. Humana Press eBooks. 163. 243–252. 6 indexed citations
16.
Harvey, Ben‐Gary, Philip L. Leopold, Neil R. Hackett, et al.. (1999). Airway epithelial CFTR mRNA expression in cystic fibrosis patients after repetitive administration of a recombinant adenovirus. Journal of Clinical Investigation. 104(9). 1245–1255. 182 indexed citations
17.
Williams, P. Mickey, et al.. (1996). A novel method for real time quantitative RT-PCR.. Genome Research. 6(10). 995–1001. 1747 indexed citations breakdown →
18.
Williams, P. Mickey, et al.. (1995). Single strand conformational polymorphism using capillary electrophoresis with two‐dye laser‐induced fluorescence detection. Electrophoresis. 16(1). 1429–1436. 65 indexed citations
20.
Williams, P. Mickey, Marc Navre, & G M Ringold. (1991). Glucocorticoid Induction of the Adipocyte Clone 5 Gene Requires High Cell Density. Molecular Endocrinology. 5(5). 615–618. 8 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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