Ian W. Taylor

9.0k total citations · 3 hit papers
88 papers, 7.5k citations indexed

About

Ian W. Taylor is a scholar working on Molecular Biology, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Ian W. Taylor has authored 88 papers receiving a total of 7.5k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 35 papers in Oncology and 18 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Ian W. Taylor's work include Lung Cancer Treatments and Mutations (18 papers), Colorectal Cancer Treatments and Studies (16 papers) and Cancer Genomics and Diagnostics (12 papers). Ian W. Taylor is often cited by papers focused on Lung Cancer Treatments and Mutations (18 papers), Colorectal Cancer Treatments and Studies (16 papers) and Cancer Genomics and Diagnostics (12 papers). Ian W. Taylor collaborates with scholars based in United Kingdom, Australia and United States. Ian W. Taylor's co-authors include David W. Hedley, Michael Friedländer, Catherine A. Rugg, Elizabeth A. Musgrove, Robert L. Sutherland, Jeffrey L. Wrana, Rosemary E. Hall, Yongmei Liu, Bruce Milthorpe and Joseph O’Connell and has published in prestigious journals such as Science, Cell and Journal of Clinical Oncology.

In The Last Decade

Ian W. Taylor

87 papers receiving 7.2k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Method for analysis of cellular DNA content of paraffin-embedded pathological material using flow cytometry.

1983 1.8k citations David W. Hedley, Ian W. Taylor et al. profile →
High-Throughput Mapping of a Dynamic Signaling Network in Mammalian Cells

2005 553 citations Miriam Barrios‐Rodiles, Kevin R. Brown et al. Science profile →
Dynamic modularity in protein interaction networks predicts breast cancer outcome

2009 544 citations Ian W. Taylor, Yongmei Liu et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ian W. Taylor United Kingdom	38	3.4k	2.4k	1.8k	1.7k	1.1k	88	7.5k
Christopher S. Foster United Kingdom	46	3.9k 1.2×	1.7k 0.7×	1.9k 1.0×	2.8k 1.6×	470 0.4×	150	7.4k
Garret M. Hampton United States	45	5.6k 1.7×	2.6k 1.1×	1.9k 1.0×	1.2k 0.7×	898 0.8×	93	9.1k
David Chang United States	38	5.5k 1.6×	3.1k 1.3×	1.2k 0.6×	1.1k 0.6×	1.1k 1.0×	84	9.6k
Eliot M. Rosen United States	57	4.7k 1.4×	1.8k 0.7×	1.2k 0.7×	999 0.6×	654 0.6×	145	7.9k
Generoso Bevilacqua Italy	49	5.5k 1.6×	3.8k 1.6×	1.9k 1.0×	2.1k 1.2×	1.9k 1.7×	283	10.3k
Anatoly Dritschilo United States	49	4.6k 1.4×	2.7k 1.1×	1.6k 0.8×	1.7k 1.0×	456 0.4×	280	8.3k
Angelo Paradiso Italy	45	3.9k 1.2×	2.9k 1.2×	2.0k 1.1×	1.0k 0.6×	652 0.6×	336	7.8k
Jan P. A. Baak Netherlands	46	2.0k 0.6×	2.1k 0.9×	2.2k 1.2×	797 0.5×	1.3k 1.2×	236	6.8k
John S. Welch United States	32	5.6k 1.7×	1.9k 0.8×	2.8k 1.5×	921 0.5×	853 0.8×	141	10.2k
Steven de Jong Netherlands	53	5.2k 1.5×	3.3k 1.4×	1.9k 1.0×	1.0k 0.6×	730 0.7×	188	9.1k

Countries citing papers authored by Ian W. Taylor

Since Specialization

Citations

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

Fields of papers citing papers by Ian W. Taylor

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ian W. Taylor. 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 Ian W. Taylor. The network helps show where Ian W. Taylor may publish in the future.

Co-authorship network of co-authors of Ian W. Taylor

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

All Works

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20 of 20 papers shown

Holmes, Amanda, et al.. (2019). Increasing HD-BIOP3 Seeding Efficiencies Using the VIPS™. Genetic Engineering & Biotechnology News. 39(8). 60–62. 1 indexed citations

Taylor, Ian W., et al.. (2015). Paradigm Shift for Cell-Line Development. Genetic Engineering & Biotechnology News. 36(1). 24–25. 2 indexed citations

Kris, Mark G., D. Ross Camidge, Giuseppe Giaccone, et al.. (2015). Targeting HER2 aberrations as actionable drivers in lung cancers: phase II trial of the pan-HER tyrosine kinase inhibitor dacomitinib in patients with HER2-mutant or amplified tumors. Annals of Oncology. 26(7). 1421–1427. 221 indexed citations

Ramalingam, Suresh S., Pasi A. Jänne, Tony Mok, et al.. (2014). Randomized, double-blinded study of dacomitinib, an irreversible pan-human epidermal growth factor receptor (HER) inhibitor, versus erlotinib for second-line/third-line therapy of locally advanced/metastatic non-small cell lung cancer (ARCHER 1009).. Journal of Clinical Oncology. 32(15_suppl). 8018–8018. 13 indexed citations

Ramalingam, Suresh S., Pasi A. Jänne, Tony Mok, et al.. (2014). Dacomitinib versus erlotinib in patients with advanced-stage, previously treated non-small-cell lung cancer (ARCHER 1009): a randomised, double-blind, phase 3 trial. The Lancet Oncology. 15(12). 1369–1378. 111 indexed citations

Kris, Mark G., Zelanna Goldberg, Pasi A. Jänne, et al.. (2012). Dacomitinib (PF-00299804), An Irreversible Pan-Her Tyrosine Kinase Inhibitor (TKI), For First-Line Treatment of EGFR-Mutant or Her2-Mutant or -Amplified Lung Cancers. Annals of Oncology. 23. ix400–ix401. 18 indexed citations

Savas, Sevtap, Ian W. Taylor, Jeffrey L. Wrana, & Hilmi Özçelik. (2006). Functional nonsynonymous single nucleotide polymorphisms from the TGF-β protein interaction network. Physiological Genomics. 29(2). 109–117. 10 indexed citations

Hewitt, Christopher J., Helen Onyeaka, G.R. Lewis, Ian W. Taylor, & Alvin W. Nienow. (2006). A comparison of high cell density fed‐batch fermentations involving both induced and non‐induced recombinant Escherichia coli under well‐mixed small‐scale and simulated poorly mixed large‐scale conditions. Biotechnology and Bioengineering. 96(3). 495–505. 41 indexed citations

Barrios‐Rodiles, Miriam, Kevin R. Brown, Barish Ozdamar, et al.. (2005). High-Throughput Mapping of a Dynamic Signaling Network in Mammalian Cells. Science. 307(5715). 1621–1625. 553 indexed citations breakdown →

10.

Francis, D., Dimitris Visvikis, Durval C. Costa, et al.. (2004). Assessment of recurrent colorectal cancer following 5-fluorouracil chemotherapy using both 18 FDG and 18 FLT PET. European Journal of Nuclear Medicine and Molecular Imaging. 31(6). 928–928. 15 indexed citations

11.

Visvikis, Dimitris, et al.. (2002). Quantitative comparison of 18FDG and 18FLT in colorectal carcinoma. UCL Discovery (University College London). 2 indexed citations

12.

Middleton, Brian, et al.. (2002). Identification of in Vitro Folding Conditions for Procathepsin S and Cathepsin S Using Fractional Factorial Screens. Protein Expression and Purification. 24(2). 242–254. 42 indexed citations

13.

Weston, Simon A., Roger Camble, Ian W. Taylor, et al.. (1998). Crystal structure of the anti-fungal target N-myristoyl transferase. Nature Structural Biology. 5(3). 213–221. 93 indexed citations

14.

Holdgate, Geoffrey A., Alan Riboldi‐Tunnicliffe, Walter H.J. Ward, et al.. (1997). The Entropic Penalty of Ordered Water Accounts for Weaker Binding of the Antibiotic Novobiocin to a Resistant Mutant of DNA Gyrase: A Thermodynamic and Crystallographic Study. Biochemistry. 36(32). 9663–9673. 184 indexed citations

15.

Taylor, Ian W., Costas Ioannides, & D. V. Parke. (1989). Organic nitrate reductase: Reassessment of its subcellular localization and tissue distribution and its relationship to the glutathione transferases. International Journal of Biochemistry. 21(1). 67–71. 14 indexed citations

16.

Morris, Valerie B. & Ian W. Taylor. (1985). Estimation of nonproliferating cells in the neural retina of embryonic chicks by flow cytometry. Cytometry. 6(4). 375–380. 9 indexed citations

17.

Stuart‐Harris, R., David W. Hedley, Ian W. Taylor, Arnold Levene, & I. E. Smith. (1985). Tumour ploidy, response and survival in patients receiving endocrine therapy for advanced breast cancer. British Journal of Cancer. 51(4). 573–576. 33 indexed citations

18.

Hacking, Andrew J., et al.. (1984). Selection of yeast able to produce ethanol from glucose at 40� C. Applied Microbiology and Biotechnology. 19(5). 53 indexed citations

19.

Sutherland, Robert L., Rosemary E. Hall, & Ian W. Taylor. (1983). Cell proliferation kinetics of MCF-7 human mammary carcinoma cells in culture and effects of tamoxifen on exponentially growing and plateau-phase cells.. PubMed. 43(9). 3998–4006. 243 indexed citations

20.

Fox, Richard M., Richard Kefford, E. Tripp, & Ian W. Taylor. (1981). G1-phase arrest of cultured human leukemic T-cells induced by deoxyadenosine.. PubMed. 41(12 Pt 1). 5141–50. 48 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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