Arran Turnbull

2.1k total citations
57 papers, 1.4k citations indexed

About

Arran Turnbull is a scholar working on Cancer Research, Oncology and Molecular Biology. According to data from OpenAlex, Arran Turnbull has authored 57 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Cancer Research, 32 papers in Oncology and 20 papers in Molecular Biology. Recurrent topics in Arran Turnbull's work include Breast Cancer Treatment Studies (23 papers), HER2/EGFR in Cancer Research (12 papers) and Cancer Cells and Metastasis (8 papers). Arran Turnbull is often cited by papers focused on Breast Cancer Treatment Studies (23 papers), HER2/EGFR in Cancer Research (12 papers) and Cancer Cells and Metastasis (8 papers). Arran Turnbull collaborates with scholars based in United Kingdom, United States and Japan. Arran Turnbull's co-authors include Carlos Martínez-Pérez, Simon P. Langdon, Carol Ward, James Meehan, Andrew H. Sims, J. Michael Dixon, Charlene Kay, Chrysi Xintaropoulou, Mark Gray and Lorna Renshaw and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and Cancer Research.

In The Last Decade

Arran Turnbull

57 papers receiving 1.3k citations

Peers

Arran Turnbull
Elena Fountzilas Greece
Angel Rodriguez United States
Flavia Morales-Vásquez Mexico
Min Huang United States
Woo Chul Noh South Korea
Yue Gong China
Michaela J. Higgins United States
Yuee Teng China
Zongyue Zeng China
Pradip De United States
Elena Fountzilas Greece
Arran Turnbull
Citations per year, relative to Arran Turnbull Arran Turnbull (= 1×) peers Elena Fountzilas

Countries citing papers authored by Arran Turnbull

Since Specialization
Citations

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

Fields of papers citing papers by Arran Turnbull

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arran Turnbull

This figure shows the co-authorship network connecting the top 25 collaborators of Arran Turnbull. A scholar is included among the top collaborators of Arran Turnbull 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 Arran Turnbull. Arran Turnbull 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.
Mahesh, Arun, et al.. (2024). Basal–epithelial subpopulations underlie and predict chemotherapy resistance in triple-negative breast cancer. EMBO Molecular Medicine. 16(4). 823–853. 8 indexed citations
2.
Kay, Charlene, Carlos Martínez-Pérez, J. Michael Dixon, & Arran Turnbull. (2023). The Role of Nodes and Nodal Assessment in Diagnosis, Treatment and Prediction in ER+, Node-Positive Breast Cancer. Journal of Personalized Medicine. 13(10). 1476–1476. 4 indexed citations
3.
He, Xiaping, Lorna Renshaw, Carlos Martínez-Pérez, et al.. (2022). Integrated DNA and RNA Sequencing Reveals Drivers of Endocrine Resistance in Estrogen Receptor–Positive Breast Cancer. Clinical Cancer Research. 28(16). 3618–3629. 11 indexed citations
4.
Vesnin, Sergey, et al.. (2022). Passive Microwave Radiometry and microRNA Detection for Breast Cancer Diagnostics. Diagnostics. 13(1). 118–118. 1 indexed citations
5.
Meehan, James, Mark Gray, Carlos Martínez-Pérez, et al.. (2021). A Novel Approach for the Discovery of Biomarkers of Radiotherapy Response in Breast Cancer. Journal of Personalized Medicine. 11(8). 796–796. 10 indexed citations
6.
Dixon, J. Michael, et al.. (2020). Factors affecting the number of sentinel lymph nodes removed in patients having surgery for breast cancer. Breast Cancer Research and Treatment. 184(2). 335–343. 11 indexed citations
7.
Gray, Mark, James Meehan, Arran Turnbull, et al.. (2020). The Importance of the Tumor Microenvironment and Hypoxia in Delivering a Precision Medicine Approach to Veterinary Oncology. Frontiers in Veterinary Science. 7. 598338–598338. 5 indexed citations
8.
Gray, Mark, James Meehan, Carlos Martínez-Pérez, et al.. (2020). Naturally-Occurring Canine Mammary Tumors as a Translational Model for Human Breast Cancer. Frontiers in Oncology. 10. 617–617. 78 indexed citations
9.
Turnbull, Arran, Samir Patel, Carlos Martínez-Pérez, Anne Rigg, & Olga Oikonomidou. (2020). Risk of chemotherapy-related amenorrhoea (CRA) in premenopausal women undergoing chemotherapy for early stage breast cancer. Breast Cancer Research and Treatment. 186(1). 237–245. 8 indexed citations
10.
Al‐Lamki, Rafia S., Nicholas J. Hudson, John R. Bradley, et al.. (2020). The Efficacy of Sunitinib Treatment of Renal Cancer Cells Is Associated with the Protein PHAX In Vitro. Biology. 9(4). 74–74. 3 indexed citations
11.
Inda, Márcia A., Erik J. Blok, Peter J.K. Kuppen, et al.. (2019). Estrogen Receptor Pathway Activity Score to Predict Clinical Response or Resistance to Neoadjuvant Endocrine Therapy in Primary Breast Cancer. Molecular Cancer Therapeutics. 19(2). 680–689. 39 indexed citations
12.
Dixon, J. Michael, David Cameron, Laura Arthur, et al.. (2019). Accurate Estrogen Receptor Quantification in Patients with Negative and Low-Positive Estrogen-Receptor-Expressing Breast Tumors: Sub-Analyses of Data from Two Clinical Studies. Advances in Therapy. 36(4). 828–841. 12 indexed citations
13.
Turnbull, Arran, et al.. (2019). On-treatment biomarkers can improve prediction of response to neoadjuvant chemotherapy in breast cancer. Breast Cancer Research. 21(1). 73–73. 38 indexed citations
14.
Martínez-Pérez, Carlos, Arran Turnbull, & J. Michael Dixon. (2018). The evolving role of receptors as predictive biomarkers for metastatic breast cancer. Expert Review of Anticancer Therapy. 19(2). 121–138. 11 indexed citations
15.
Arthur, Laura, Arran Turnbull, Lucy R. Khan, & J. Michael Dixon. (2017). Pre-operative Endocrine Therapy. Current Breast Cancer Reports. 9(4). 202–209. 17 indexed citations
16.
Varešlija, Damir, Jean McBryan, Ailís Fagan, et al.. (2016). Adaptation to AI Therapy in Breast Cancer Can Induce Dynamic Alterations in ER Activity Resulting in Estrogen-Independent Metastatic Tumors. Clinical Cancer Research. 22(11). 2765–2777. 17 indexed citations
17.
Um, In Hwa, Dana Faratian, Ying Zhou, et al.. (2015). Multi-Scale Genomic, Transcriptomic and Proteomic Analysis of Colorectal Cancer Cell Lines to Identify Novel Biomarkers. PLoS ONE. 10(12). e0144708–e0144708. 41 indexed citations
18.
Arthur, Laura, Arran Turnbull, Alexey A. Larionov, et al.. (2014). Molecular Changes in Lobular Breast Cancers in Response to Endocrine Therapy. Cancer Research. 74(19). 5371–5376. 25 indexed citations
19.
Caie, Peter D., Arran Turnbull, Susan M. Farrington, Anca Oniscu, & David J. Harrison. (2014). Quantification of tumour budding, lymphatic vessel density and invasion through image analysis in colorectal cancer. Journal of Translational Medicine. 12(1). 156–156. 42 indexed citations
20.
Turnbull, Arran, Robert R. Kitchen, Alexey A. Larionov, et al.. (2012). Direct integration of intensity-level data from Affymetrix and Illumina microarrays improves statistical power for robust reanalysis. BMC Medical Genomics. 5(1). 35–35. 35 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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