P. M. Wilson

626 total citations
19 papers, 441 citations indexed

About

P. M. Wilson is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, P. M. Wilson has authored 19 papers receiving a total of 441 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Oncology, 6 papers in Pulmonary and Respiratory Medicine and 5 papers in Molecular Biology. Recurrent topics in P. M. Wilson's work include Colorectal Cancer Treatments and Studies (4 papers), Gastric Cancer Management and Outcomes (3 papers) and Hepatocellular Carcinoma Treatment and Prognosis (2 papers). P. M. Wilson is often cited by papers focused on Colorectal Cancer Treatments and Studies (4 papers), Gastric Cancer Management and Outcomes (3 papers) and Hepatocellular Carcinoma Treatment and Prognosis (2 papers). P. M. Wilson collaborates with scholars based in United States, United Kingdom and Switzerland. P. M. Wilson's co-authors include Yin Fang, ME Hatten, R. H. Fryer, Dongyun Yang, Heinz‐Josef Lenz, Job Thomas, Yan Ning, Melissa J. LaBonte, Eric K. Rowinsky and Siwen Hu‐Lieskovan and has published in prestigious journals such as Journal of Clinical Oncology, Journal of Neuroscience and British Journal of Cancer.

In The Last Decade

P. M. Wilson

18 papers receiving 420 citations

Peers

P. M. Wilson

ONCOL

PRM

GENET

Caterina Miro Italy

Jiwen Li China

Fenghua Zhao China

Eun‐Young Kim South Korea

Kevin C.M. Hermans Netherlands

Karin Hultman Sweden

Julian Vallejo United States

Yanwu You China

Devi Prasadh Ramakrishnan United States

Caterina Miro Italy

P. M. Wilson

167 ×0.8

66 ×0.5

80 ×0.9

ONCOL

65 ×1.3

PRM

37 ×0.8

GENET

Citations per year, relative to P. M. Wilson P. M. Wilson (= 1×) peers Caterina Miro

Countries citing papers authored by P. M. Wilson

Since Specialization

Citations

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

Fields of papers citing papers by P. M. Wilson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of P. M. Wilson

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

All Works

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19 of 19 papers shown

Benhaïm, Léonor, W Zhang, Takeru Wakatsuki, et al.. (2014). Genetic variants of kinase suppressors of Ras (KSR1) to predict survival in patients with ERα-positive advanced breast cancer. The Pharmacogenomics Journal. 15(3). 235–240. 2 indexed citations

Winder, Thomas, Georgios Giamas, P. M. Wilson, et al.. (2013). Insulin-like growth factor receptor polymorphism defines clinical outcome in estrogen receptor-positive breast cancer patients treated with tamoxifen. The Pharmacogenomics Journal. 14(1). 28–34. 30 indexed citations

Thomas, Job & P. M. Wilson. (2013). Construction waste management in India. Dyuthi Digital Repository (Cochin University of Science and Technology). 19 indexed citations

Wilson, P. M., Dongyun Yang, Mizutomo Azuma, et al.. (2012). Intratumoral expression profiling of genes involved in angiogenesis in colorectal cancer patients treated with chemotherapy plus the VEGFR inhibitor PTK787/ZK 222584 (vatalanib). The Pharmacogenomics Journal. 13(5). 410–416. 16 indexed citations

Winder, Thomas, P. M. Wilson, Dongyun Yang, et al.. (2012). An individual coding polymorphism and the haplotype of the SPARC gene predict gastric cancer recurrence. The Pharmacogenomics Journal. 13(4). 342–348. 5 indexed citations

Wilson, P. M., et al.. (2012). Liver Toxicity in Patients with Metastatic Renal Cell Carcinoma Treated with Pazopanib Therapy. Annals of Oncology. 23. ix290–ix290. 1 indexed citations

Winder, Thomas, Pierre Bohanes, Dongyun Yang, et al.. (2011). GRP78 promoter polymorphism rs391957 as potential predictor for clinical outcome in gastric and colorectal cancer patients. Annals of Oncology. 22(11). 2431–2439. 26 indexed citations

LaBonte, Melissa J., P. M. Wilson, Dongyun Yang, et al.. (2011). The Cyclin D1 (CCND1) A870G polymorphism predicts clinical outcome to lapatinib and capecitabine in HER2-positive metastatic breast cancer. Annals of Oncology. 23(6). 1455–1464. 10 indexed citations

Gerger, Armin, W. Zhang, Pierre Bohanes, et al.. (2011). Angiogenesis gene polymorphisms and clinical outcome of metastatic colorectal cancer treated with first-line bevacizumab and oxaliplatin-based chemotherapy.. Journal of Clinical Oncology. 29(15_suppl). 3592–3592. 2 indexed citations

10.

Winder, Thomas, Yan Ning, Dongyun Yang, et al.. (2010). A let-7 microRNA-binding site polymorphism in 3′-untranslated region of KRAS gene predicts response in wild-type KRAS patients with metastatic colorectal cancer treated with cetuximab monotherapy. Annals of Oncology. 22(1). 104–109. 107 indexed citations

11.

Wilson, P. M., R. H. Fryer, Yin Fang, & ME Hatten. (2010). Astn2, A Novel Member of the Astrotactin Gene Family, Regulates the Trafficking of ASTN1 during Glial-Guided Neuronal Migration. Journal of Neuroscience. 30(25). 8529–8540. 109 indexed citations

12.

Yang, Dong‐Hua, Thomas Winder, Pierre Bohanes, et al.. (2010). Correlations of mRNA expression levels of genes in the targeted pathways and Kras mutation status in patients with colorectal cancer.. Journal of Clinical Oncology. 28(15_suppl). 10641–10641. 1 indexed citations

13.

Moon, Rebecca J, P. M. Wilson, Fenella J. Kirkham, & Justin H. Davies. (2008). Growth monitoring following traumatic brain injury. Archives of Disease in Childhood. 94(9). 699–701. 16 indexed citations

14.

Wilson, P. M., Di Yang, M. Shi, et al.. (2008). Use of intratumoral mRNA expression of genes involved in angiogenesis and HIF1 pathway to predict outcome to VEGFR tyrosine kinase inhibitor (TKI) in patients enrolled in CONFIRM1 and CONFIRM2. Journal of Clinical Oncology. 26(15_suppl). 4002–4002. 10 indexed citations

15.

Stephens, Robert, Katy Fidler, P. M. Wilson, et al.. (2006). Endotoxin immunity and the developmentof the systemic inflammatory responsesyndrome in critically ill children. Intensive Care Medicine. 32(2). 286–294. 16 indexed citations

16.

Wilson, P. M., et al.. (2003). Case report of a 13‐year‐old struck by lightning. Pediatric Anesthesia. 13(1). 76–79. 14 indexed citations

17.

Eatock, Martin, et al.. (2000). True. British Journal of Cancer. 82(12). 1925–1931. 14 indexed citations

18.

Morris, Erick J., et al.. (1999). Optimization of Single-Cell Gel Electrophoresis (SCGE) for Quantitative Analysis of Neuronal DNA Damage. BioTechniques. 26(2). 282–289. 41 indexed citations

19.

Wilson, P. M., et al.. (1983). Relative Proportions of Human Hemoglobins A, S, C in Individual Erythrocytes of Heterozygotes. Hemoglobin. 7(3). 227–244. 2 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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