Georgette Tanner

1.3k total citations
8 papers, 48 citations indexed

About

Georgette Tanner is a scholar working on Cancer Research, Molecular Biology and Genetics. According to data from OpenAlex, Georgette Tanner has authored 8 papers receiving a total of 48 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cancer Research, 4 papers in Molecular Biology and 3 papers in Genetics. Recurrent topics in Georgette Tanner's work include Cancer Genomics and Diagnostics (4 papers), Glioma Diagnosis and Treatment (3 papers) and Ferroptosis and cancer prognosis (3 papers). Georgette Tanner is often cited by papers focused on Cancer Genomics and Diagnostics (4 papers), Glioma Diagnosis and Treatment (3 papers) and Ferroptosis and cancer prognosis (3 papers). Georgette Tanner collaborates with scholars based in United Kingdom and United States. Georgette Tanner's co-authors include Lucy F. Stead, David R. Westhead, Alastair Droop, Paolo Actis, Iain C. Macaulay, Andrew J. Bulpitt, Chalmers Chau, Morag Taylor, Ian Carr and Aruna Chakrabarty and has published in prestigious journals such as Nature Communications, Bioinformatics and Science Advances.

In The Last Decade

Georgette Tanner

8 papers receiving 47 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Georgette Tanner United Kingdom	4	26	20	9	7	6	8	48
Yipei Song China	4	30 1.2×	17 0.8×	6 0.7×	6 0.9×	5 0.8×	10	65
Katherine Pogrebniak United States	2	34 1.3×	28 1.4×	7 0.8×	17 2.4×	3 0.5×	3	69
Maihi Fujita United States	2	24 0.9×	22 1.1×	10 1.1×	28 4.0×	2 0.3×	6	55
Shahab Falahi Iran	4	50 1.9×	41 2.0×	10 1.1×	9 1.3×	5 0.8×	5	79
Taeseob Lee South Korea	4	17 0.7×	15 0.8×	3 0.3×	3 0.4×	3 0.5×	6	31
Chi-Yun Wu Taiwan	3	47 1.8×	30 1.5×	4 0.4×	7 1.0×	2 0.3×	5	58
Joanna Schmidt United States	3	48 1.8×	12 0.6×	2 0.2×	8 1.1×	8 1.3×	8	60
Sireesha Yalavarthi United States	3	32 1.2×	10 0.5×	4 0.4×	29 4.1×	6 1.0×	9	56
Mengge Lyu China	5	66 2.5×	17 0.8×	4 0.4×	6 0.9×	4 0.7×	6	103
Stefanos A. Bamopoulos Germany	3	25 1.0×	13 0.7×	2 0.2×	7 1.0×	3 0.5×	4	44

Countries citing papers authored by Georgette Tanner

Since Specialization

Citations

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

Fields of papers citing papers by Georgette Tanner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Georgette Tanner

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Tanner, Georgette, et al.. (2025). GBMPurity: A machine learning tool for estimating glioblastoma tumor purity from bulk RNA-sequencing data. Neuro-Oncology. 27(6). 1458–1473. 3 indexed citations

2.

Chau, Chalmers, Georgette Tanner, Morag Taylor, et al.. (2024). Single-cell nanobiopsy enables multigenerational longitudinal transcriptomics of cancer cells. Science Advances. 10(10). eadl0515–eadl0515. 17 indexed citations

3.

Thomas, Morgan, Martina Finetti, Steven Pollock, et al.. (2023). PREDICTING GLIOBLASTOMA GENE EXPRESSION THERAPY RESPONSE WITH MACHINE LEARNING. Neuro-Oncology. 25(Supplement_3). iii13–iii14. 1 indexed citations

4.

Tanner, Georgette, David R. Westhead, Alastair Droop, & Lucy F. Stead. (2021). Benchmarking pipelines for subclonal deconvolution of bulk tumour sequencing data. Nature Communications. 12(1). 6396–6396. 13 indexed citations

5.

Cummings, Michele, et al.. (2020). Decreasing formalin concentration improves quality of DNA extracted from formalin-fixed paraffin-embedded tissue specimens without compromising tissue morphology or immunohistochemical staining. Journal of Clinical Pathology. 73(8). 514–518. 4 indexed citations

6.

Barthel, Floris P, Kevin C. Johnson, Frederick S. Varn, et al.. (2019). GENE-28. LONGITUDINAL MOLECULAR TRAJECTORIES OF DIFFUSE GLIOMA IN ADULTS. Neuro-Oncology. 21(Supplement_6). vi103–vi103. 3 indexed citations

7.

Tanner, Georgette, David R. Westhead, Alastair Droop, & Lucy F. Stead. (2019). Simulation of heterogeneous tumour genomes with HeteroGenesis and in silico whole exome sequencing. Bioinformatics. 35(16). 2850–2852. 4 indexed citations

8.

Droop, Alastair, Alexander Bruns, Georgette Tanner, et al.. (2017). How to analyse the spatiotemporal tumour samples needed to investigate cancer evolution: A case study using paired primary and recurrent glioblastoma. International Journal of Cancer. 142(8). 1620–1626. 3 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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